Research Article Evaluating Green Performance of Suppliers via Analytic … · 2019. 7. 31. · system [ ], analytic hierarchy process (AHP) [ ], fuzzy AHP [, ], a hybrid fuzzy analytic

Hindawi Publishing CorporationJournal of Industrial EngineeringVolume 2013 Article ID 915241 13 pageshttpdxdoiorg1011552013915241

Research ArticleEvaluating Green Performance of Suppliers via AnalyticNetwork Process and TOPSIS

GuumllGen Akman and Hamit PJGkJn

Department of Industrial Engineering Faculty of Engineering Kocaeli University 41380 Kocaeli Turkey

Correspondence should be addressed to Gulsen Akman akmangkocaeliedutr

Received 15 August 2012 Revised 29 January 2013 Accepted 25 February 2013

Academic Editor C K Kwong

Copyright copy 2013 G Akman and H Pıskın This is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work is properlycited

Developments in environmental issues in the last few years have been forcing manufacturing companies to improve theirenvironmental performances Many firms developed integrated relationships with their suppliers to increase their environmentalperformance and to decrease their hazardous effects on the environmentThen selecting suitable and green suppliers in the supplychain has become a key strategic consideration A performance evaluation system for green suppliers is necessary to determine thesuitability of suppliers to cooperate with the firmTherefore in this study a model for evaluating green performance of suppliers isproposed and a hybrid multicriteria decision making model is developed in order to evaluate green performance of the suppliersThe analytical network process technique is applied to handle the relationships and dependence of selection criteria and subcriteriaand determine weights of the criteria The technique for order preference by similarity to ideal solution is used to sequencethe suppliers for ideal solution of the suppliersrsquo green performance evaluation problem After a comprehensive literature surveyevaluation criteria of green performance for suppliers are determined Finally green performance of 18 suppliers of an automobilecompany was evaluated by this model These 18 suppliers manufacture chassis and its components

1 Introduction

In recent years because of growing worldwide awarenessof environmental protection increasing government regula-tions and stronger public awareness in environmental pro-tection firms today cannot disregard environmental issuesand they have to pay attention to environmental issues inorder to survive in the global market [1] Therefore inthe world there is a growing interest in the green supplychain management (GSCM) and the green issue has becomemore and more critical in supply chain management (SCM)[2] Over the last decade linking supply chain activitiesand environmental issues such as green purchasing reverselogistics product stewardship and design for the environ-ment have been a topic of interest among many manu-facturing organizations [3] In order to decrease hazardousenvironmental effects firms have been forced to improvetheir environmental issues like decreasing hazardous impacts

of their products their manufacturing processes logisticsprocesses and so forth [4]

Environmental performance of a company can be deter-mined by its own environmental efforts and environmentalperformance of its suppliers For manufacturing industriesgreen manufacturing (ie manufacturing is environmentallyresponsible) and concerned processes need green supplychain (GSC) and studying suppliers with green abilities[5] Therefore companies have to establish close and inte-grated relationships with their supplier to develop theirenvironmental performance They have to evaluate greenperformance of their suppliers Thus there is an increasingneed of a performance evaluation system for green suppliersto determine the suitability of suppliers to cooperate with thefirm [6]

In the literature while there are too many studies aboutsupplier selection and evaluation the number of studiesabout green supplier selection and evaluation is very limited

2 Journal of Industrial Engineering

Therefore this study was performed in the area of green sup-plier performance Our contributions from this study include(1) modeling the decision problem within the context of aGSCM decision and (2) evaluation of supplier performanceby the view point of environmental issues

In the green supply chain literature various techniquesare used to evaluate and select green suppliers such as ratingsystem [4] analytic hierarchy process (AHP) [7] fuzzy AHP[8 9] a hybrid fuzzy analytic network process (ANP) andfuzzy Preference Ranking Organization method for enrich-ment evaluations (PROTMETHEE) [10] fuzzy extendedAHP [1] fuzzy goal programming [11] artificial neuralnetwork data envelopment analysis and analytic netwokprocess (ANP) [2] Rough set theory [12] fuzzy Techniquefor Order Preference by similarity to ideal solution (TOPSIS)[13] an integrated model of fuzzy decision making trial andevaluation laboratory (DEMATEL) ANP TOPSIS [5] a grey-based DEMATEL approach [14] Grey approach [15] fuzzyAHP and fuzzy multiobjective linear programming [16]

Because there are both qualitative and quantitative factorsthat influence the evaluation and selection of green suppliersevaluation and selection problem of green supplier is a multi-criteria decision making (MCDM) problem Thus there is aneed to employ MCDM techniques to tackle green supplierselection problem appropriately Firstly ANP technique [17]is applied to handle the relationships and dependence of se-lection criteria and subcriteria and to determine weightsof criteria Then TOPSIS technique is used to sequencethe suppliers for ideal solution of the supplier evaluationproblem

The paper is organized as follows The paper beginswith the literature research about GSCM Then after abrief literature review of methodologies used evaluation ofsupplierrsquos environmental performance and selection of greensupplier are examined to develop a structure for evaluatinggreen supplier performance and selecting green suppliersThe next section illustrates the proposed green supplierevaluation and selection methodology through the case ofan automobile company in Turkey The paper finishes by adiscussion section

2 Literature Review

21 Green Supply Chain Green et al [18] defined greensupply as ldquothe way in which innovations in SCM andindustrial purchasing may be considered in the context ofthe environmentrdquo Srivastava [19] defined GSCM as ldquointegrat-ing environmental thinking into supply chain managementincluding product design material sourcing and selectionmanufacturing processes delivery of the final product to theconsumers and end-of-life management of the product afterits useful liferdquo Also many researchers have defined a GSCMin various manners using different terms [20] GSCM can bedefined as integrating environmental issues into supply chainmanagement Originally GSCM was bounded to purchasingissues Hervani et al [21] defined GSCM as integratingsuppliers into environmental management processes Rettaband Ben Brik [22] defined the GSC as a managerial approachthat seeks to minimize a product or servicersquos environmental

effect The bottom line of these definitions is the same thatis ldquoenvironmentrdquo GSCM contains the activities such as wastereduction recycling reuse and the substitution of materials[23] and it includes green purchasing green manufacturingandmaterialmanagement green distribution andmarketingand reverse logistics [24]

According to Narasimhan and Carter [23] GSCMincludes ldquothe purchasing functionrsquos involvement in activitiesthat include reduction recycling reuse and the substitutionof materialsrdquoThemost common GSCM practices are to eval-uate the environmental performance of suppliers to requiresuppliers to acceptmeasures providing environmental qualityof their supplied products and to evaluate the cost of waste intheirmanufacturing processes [7] However GSCMpracticesalso extend to the entire value chain (from supplier toconsumer) when organizations inform buyers of ways toreduce their impacts on the natural environment [25]

Hall [26] investigated the circumstances under whichldquoenvironmental supply chain dynamicsrdquo emerge He arguedthat environmental supply chain dynamics emerge whenenvironmental pressures are synthesized with supply chainpressures which have had considerable influence on thesupply base on the strength of case studies in the Britishand Japanese food retail sector and the British aerospaceindustry Zhu et al [27] expressed that ldquorange of GSCMchanges from green purchasing (GP) to integrated life-cyclemanagement supply chains flowing from supplier throughto manufacturer customer and closing the loop with reverselogisticsrdquo

According to Vachon and Klassen [3] suppliers manu-facturers and customers should collaborate to reduce haz-ardous environmental effects from manufacturing processesand products

22 Evaluation of Green Supplier Performance Supplier eval-uation process is an important element in supplier-basedmanufacturing and SCM has been gaining attention inboth the academic literature and industrial practice Thesupplier selection decision is one of the critical and importantissues in SCM for many organizations to help maintain astrategically competitive position [28] It becomes one of themost important components of production and operationsmanagement for many organizations Supplier selection andevaluation process is the process by which the companyidentifies evaluates and contracts suppliers

Measuring and understanding supplier performance iscrucial to provide a well-functioning supply chain and todevelop competitive position of a company The goal of thesupplier evaluation is to develop the performance of keysuppliers [29] Companies have some advantages throughevaluating their suppliers They have better visibility intosupplier performance decrease risk reduce order cycle timesand inventory and thus increase competitive advantage andcoordinate practices between themselves and their suppliers[29]

In the last two decades there is increasing attentionto evaluate suppliersrsquo green performance There are lotsof studies related this topics in the literature A detailedliterature search was performed about the concepts of GSC

Journal of Industrial Engineering 3Ta

ble1Cr

iteria

used

toevaluategreensupp

liers

Author(s)

Azzon

eand

Noci1996

[42]

Noci1997

[4]

Hum

preyse

tal2003

[30]

Zhuand

Sarkis

2004

[43]

Hum

phreys

etal

2003

[31]

Tuzkayae

tal

2009

[10]

Leee

tal

2009

[1]

Kuoetal

2010

[2]

Baiand

Sarkis

2010

[12]

Fuetal

2012

[14]

Buyuko

zkan

andCiftc

i2012

[5]

Evaluatio

ncriteria

(i)ldquoExternalrdquo

environm

en-

tal

effectiv

eness

(ii)E

nviro

n-mental

efficiency

(iii)ldquoG

reenrdquo

image

(iv)E

nviro

n-mental

flexibility

(i)Green

competencies

(ii)C

urrent

environm

en-

talefficiency

(iii)Supp

lierrsquos

greenim

age

(iv)N

etlife

cycle

cost

(i)En

viron-

mental

competen-

cies

(ii)M

anage-

ment

decisio

ns(iii)Green

image

(iv)D

esign

for

environm

ent

(v)E

nviro

n-mental

managem

ent

syste

m

(i)Internal

environm

ental

managem

ent

(ii)ISO

14001

certificatio

n(iii)Ex

ternal

GSC

Mpractic

es(iv

)Investm

ent

recovery

(v)E

codesig

n

(i)En

vironm

ental

costs

(pollutant

effects)

(ii)E

nviro

nmental

costs

(improvem

ent)

(iii)Managem

ent

competencies

(iv)G

reen

image

(v)D

esignfor

environm

ent

(vi)En

vironm

ental

managem

ent

syste

ms

(vii)

Environm

ental

competencies

(i)Po

llutio

ncontrol

(ii)G

reen

process

managem

ent

(iii)En

viron-

mentaland

legisla

tive

managem

ent

(iv)E

nviro

n-mentalcosts

(v)G

reen

prod

uct

(vi)Green

image

(i)Quality

(ii)T

echn

o-logical

capability

(iii)To

tal

prod

uctlife

cycle

cost

(iv)G

reen

image

(v)P

ollutio

ncontrol

(vi)En

viron-

mental

managem

ent

(vii)

Green

prod

uct

(viii)G

reen

competence

(i)Quality

(ii)C

ost

(iii)Delivery

(iv)S

ervice

(v)C

orpo

rate

social

respon

sibility

(vi)

Environm

ent

(i)Green

know

ledge

transfe

rand

commun

ication

(ii)Investm

ent

andkn

owledge

transfe

r(iii)Managem

ent

and

organizatio

nal

practic

es

(i)Green

know

ledge

transfe

rand

commun

i-catio

n(ii)Invest-

mentand

resource

transfe

r(iii)Man-

agem

ent

andorga-

nizatio

nal

practic

es

(i)Organization

(ii)F

inancial

perfo

rmance

(iii)Service

quality

(iv)T

echn

olog

y(v)G

reen

competencies

Focuso

fthes

tudy

Evaluatethe

environm

en-

tal

perfo

rmance

ofa

companyrsquos

existing

operation

syste

m

Evaluate

supp

liersrsquo

environm

en-

tal

perfo

rmance

Evaluatio

nof

supp

lier

perfo

rmance

andenviron-

mental

issues

Evaluatesupp

liersrsquo

environm

ental

perfo

rmance

Evaluatio

nof

supp

liers

environm

ental

perfo

rmance

Selectingof

green

supp

liers

Evaluatin

ggreen

supp

lier

developm

ent

programsfor

organizatio

ns

Indu

stry

An

illustrative

exam

ple

An

illustrative

exam

ple

An

illustrative

exam

ple

Anillustrative

exam

ple

Whitegood

smanufacturer

Turkey

LTF-LC

Dindu

stry

Taiwan

Electro

nic

company

Taiwan

Anillustrative

exam

ple

Telecom-

mun

ica-

tions

equipm

ent

provider

China

Automotive

indu

stry

Turkey

Evaluatio

nmetho

ds

Com

paris

onof

some

techniqu

essuch

asAHP

scoring

metho

dsand

DCF

techniqu

es

Know

ledge-

based

syste

m

Know

ledge-based

syste

ms(KB

S)and

case-based

reason

ing(C

BR)

multi-attribute

analysis(M

AA)

ahybrid

fuzzy

analytic

network

processa

ndfuzzy

PROMET

HEE

Delp

himetho

dand

thefuzzy

extend

edAHP

Data

envelopm

ent

analysis

(DEA

)and

ANP

Roug

hsettheory


Table 2 Factors and subfactors for ANP

Criteria Definition

EC1

To respond in time to product or processmodifications when customer demands fromsupplier to reduce supplierrsquos environmentalimpact

EC2 Capabilities related with clean productiontechnology

EC3 Materials used in the supplied components thatreduce the impact on natural resources

EC4 Ability to alter process and products for reducingthe impact on natural resources

ECO1 Cooperation with customers for ecodesign todevelop green products

ECO2Cooperation with customers for decreasingenergy usage in supplied products and theirmanufacturing process that is cleaner production

ECO3 Cooperation with customers for green logisticsand transportation

ECO4 Cooperation with customer about environmentmanagement system and technologies

EMS1 Environment-related certificates (ie ISO 14000)

EMS2Continuous monitoring and compliance withrelated environmental legislation and legalregulations

GP1 Design of products for reuse recycle andrecovery of materials component parts

GP2 Design of products for reduced consumption ofmaterialsenergy

GP3Design of products to avoid or reduce use ofhazardous products and their manufacturingprocess

PC1 In order to prevent existence air pollutionair-pollution-control systems

PC2 Decrease water consumption and sufficiency ofwater refining plants

PC3 Evaluation and disposal system for solid wastes

PC4 Disposal of hazardous wastes according to legalregulations

Some concepts and elements were found as the basis for adecision framework for evaluating and prioritizing supplierby the company that would help to select green suppliersSome of these concepts and elements are summarized asfollows in Table 1

Noci [4] designed a conceptual approach that firstlyidentifies measures for assessing a supplierrsquos environmentalperformance and secondly suggests effective techniques fordeveloping the supplier selection procedure according to anenvironmental view point Humpreys et al [30] developed aframework from an analysis of environmental managementpractices in a number of companies along with a throughliterature surveyThen they outlined how themost importantparts of the framework were computerized using knowl-edge based systems (KBS) techniques with an evaluationof the system implemented in a multinational companyHumphreys et al [31] developed a KBS which integrates

environmental factors into the supplier selection processThesystem employs both case-based reasoning (CBR) and deci-sion support components including multiattribute analysis(MAA)

Hsu and Hu [32] proposed an ANP approach to incor-porate the issue of hazardous substance management (HSM)into supplier selectionThey presented an illustrative examplein an electronics company to demonstrate how they selecta most appropriate supplier in accordance with the require-ments of hazardous substance for environmental regulationsLee et al [1] proposed a model to select the factors forevaluating green suppliers and to evaluate the performanceof suppliers First they applied the Delphi method to selectthe most important subcriteria for traditional suppliers andfor green suppliers Then they developed a fuzzy extendedAHP model to evaluate green suppliers for a TFT-LCDmanufacturer in Taiwan Tsai andHung [11] proposed a fuzzygoal programming (FGP) approach that integrates activity-based costing (ABC) and performance evaluation in a value-chain structure for optimal green supplier selection and flowallocation Then they provide an illustrative example via agreen supply chain of a mobile phone

Tuzkaya et al [10] evaluated the environmental perfor-mance of suppliers with a hybrid fuzzy multicriteria decisionapproach fuzzy ANP and fuzzy PROMETHEEmethodologyThey used evaluation criteria such as pollution controlgreen process management environmental and legislativemanagement environmental costs green product and greenimage To foster the better understanding and the validationof the proposed methodology they presented a real-life casestudy from a white goods manufacturer of Turkey

Bai and Sarkis [12] developed a formal model usingrough set theory to investigate the relationships betweenorganizational attributes supplier development programinvolvement attributes and performance outcomes The per-formance outcomes focused on environmental and businessdimensions Their methodology generated decision rulesrelating the various attributes to the performance outcomesKuo et al [2] proposed a green supplier selection modelwhich integrates artificial neural network (ANN) and twomulti-attribute decision analysis (MADA) methods dataenvelopment analysis (DEA) and ANP The model is calledANN-MADA hybrid method

Fu et al [14] proposed a formal structured managerialapproach for organizations to help evaluate the influence ofrelationships amongst green supplier development programs(GSDPs) Utilizing GSDP categorizations they acquire mul-tifunctional managerial inputs within a telecommunicationsystems provider to evaluate the GSDPs Buyukozkan andCiftci [5] examined GSCM and GSCM capability dimensionsto propose an evaluation framework for green suppliers andused a fuzzy hybrid MCDM model based on fuzzy DEMA-TEL fuzzy ANP and fuzzy TOPSIS techniques in order toevaluate green suppliers Also they proposed application ofthe methodology for green supplier evaluation in a specificcompany in the automotive industry in Turkey The majorfive evaluation criteria for green suppliers are organizationfinancial performance service quality technology and greencompetencies Green competencies criteria contain social

Journal of Industrial Engineering 5

Table3Weightedsuperm

atrix

EC1

EC2

EC3

EC4

ECO1

ECO2

ECO3

ECO4

EMS1

EMS2

GP1

GP2

GP3

PC1

PC2

PC3

PC4

EC1

001387

001387

001387

001387

001994

012282

012500

005714

001556

00546

0002138

000000

001866

01046

00119

69000822

000000

EC2

010117

010117

010117

010117

006904

001104

002500

002857

002496

002830

006

413

007150

006001

000000

003512

004946

007753

EC3

005676

005676

005676

005676

003701

002535

002500

005714

009837

006

018

006

413

021451

006

001

003168

002275

008671

007753

EC4

002205

002205

002205

002205

007401

004

078

002500

005714

006111

005693

002138

007150

003233

005756

001628

004946

003877

ECO1

000796

004

658

004321

003594

005576

006154

002942

003630

007797

009063

001658

000000

003487

001084

000823

004

254

003527

ECO2

003893

000583

000825

001328

009425

006153

010975

0114

21003047

002483

001190

000

000

001162

003463

003662

000826

000720

ECO3

001430

000

604

000825

000

446

001112

001539

002912

001084

001359

002013

002036

000

000

001162

001295

002240

000522

001208

ECO4

001430

001702

001578

002180

003887

006154

003171

003865

007797

006

441

002091

000000

001162

001706

000823

001944

002092

EMS1

003774

005661

006

469

005032

010000

013333

00500

0013333

006

667

006

667

014461

000

000

007231

003774

002516

005661

005661

EMS2

003774

001887

001078

002516

01000

0006

667

01500

0006

667

013333

013333

000

000

000

000

007231

003774

005032

001887

001887

GP1

016380

016380

017677

010920

006

667

01000

0013333

01000

001000

0000

000

020123

042071

014184

016380

010920

016380

024571

GP2

000

000

000

000

009729

000

000

000

000

000

000

000

000

000

000

000

000

000

000

002930

006125

002364

000

000

000

000

000

000

000

000

GP3

016380

016380

005354

021840

013333

010000

006

667

010000

010000

020000

007679

016053

014184

016380

021840

016380

008190

PC1

015120

000

000

003474

008869

004541

008571

006756

010316

004

488

010924

003273

000

000

002723

014480

014480

014480

014480

PC2

015120

002907

00260

6003948

00244

7008571

009580

003788

001315

004

646

008036

000

000

013327

001958

001958

001958

001958

PC3

002520

018315

017923

013699

008472

001429

001421

003788

010939

001675

005693

000

000

007341

006516

006516

006516

006516

PC4

000000

011538

008757

006245

004541

001429

002243

002108

003258

002755

013729

000000

007341

009806

009806

009806

009806


responsibility cleanerenvironmental production and tech-nologies and environmental management system

3 Proposed Green SupplierEvaluation Framework

This study proposes a hybrid approach based on the ANPand TOPSIS methodologies to evaluate and select suppliersin the context of GSCM The general view of the proposedmethodology related with green supplier evaluation andselection is shown in Figure 1 ANP technique is applied tohandle the relationships and dependence of selection criteriaand subcriteria TOPSIS technique is applied to sequence thesuppliers for ideal solution of the green supplier performanceevaluation problem

31 Analytical Network Process (ANP) The ANP developedby Saaty and it provides a way to input judgments andmeasurements to derive ratio scale priorities for the distri-bution of influence among the factors and groups of factorsin the decision [33] ANP is an extension of AHP In realitythe factors within the hierarchy are often interdependentThe ANP method presents the network relationship betweenfactors and between groups of factors and computes therelative weightings of each factor The result of these com-putations constructs a supermatrix Finally after computingthe relationship of the supermatrix and the comprehensiveevaluations it is possible to derive the interdependence ofeach evaluation factor and options and the weighting ofpriorities Factorsalternatives are sequenced according tohigher the priority weightings In this way it is possible toselect the most appropriate alternative [34] See Tsai andChou [34] Lin et al [35] and Saaty [17 33] for further details

32 Technique for Order Preference by Similarity to IdealSolution (TOPSIS) TheTOPSIS method is based on the ideathat the chosen alternative should have the shortest distancefrom the positive ideal solution and the farthest distancefrom the negative ideal solution [36]

First a decision matrix is established for the ranking Thenormalized decision matrix 119877(= [119903

119894119895]) is calculated Then

the weighted normalized decision matrix is calculated bymultiplying the normalized decision matrix by its associatedweights After the positive ideal solutions (PIS) and nega-tive ideal solutions (NIS) are determined respectively theseparation measures are calculated using the 119898-dimensionalEuclidean distance Finally the relative closeness to the ideasolution (119862

119894) is calculated and the alternatives are ranked in

descending order The index value of 119862119894lies between 0 and 1

The larger the index value the better the performance of thealternatives You can see Chu et al [37] Jahanshahloo et al[38] for further details The TOPSIS method will be appliedto a case study which is described in detail in the applicationsection

33 Criteria of Green Supplier Evaluation Framework Whentraditional studies are investigated there are three maincriteria to evaluate and select suppliers cost quality and

ANP

TOPSIS

Step (1) Constructing ANP decision model

Step (2) Pairwise comparisons

Step (3) Constructing supermatrix

Step (4) Determining weights of criteria

Step (5) Construction of the standard decision matrix

Step (6) Construct the normalized decision matrix

Step (8) Calculate ideal positive and negative solutions

Step (9) Calculate separation measures and relativecloseness to ideal solution

Step (7) Construction of the weighted standard decisionmatrix

Figure 1 Methodology of the study

delivery [39] Additionally criteria such as customer satisfac-tion flexibility and after-sales service that are used to evaluatesuppliers are used [40] An organization may use traditionalselection criteria because of the organizationrsquos core processesrequirements These criteria generally cover issues such asquality cost delivery capacity in terms of finance servicesand equipments quantity and responsiveness Green sup-plier selection criteria are derived from an organizationaltendency to respond to any existing trends in environmentaltopics related to business management and processes

Most of the studies in the literature about evaluation ofgreen supplier performance integrates environmental criteriainto traditional supplier evaluation criteriaThey utilize tradi-tional evaluation criteria and environmental criteria togetherFor example Humpreys et al [30] Buyukozkan and Ciftci[5] Kuo et al [2] and Lee et al [1] integrated environmentalcriteria into supplier selection process and used environ-mental criteria and classical supplier development criteriatogether In the literature there is in only one study usingenvironmental criteria for evaluating supplier performanceShenc et al [41] Because of expanding studies about this areaandmaking contribution to the literature in this studywe useonly environmental criteria to evaluate supplier performancein order to develop environmental performance of the maincompany

In this study we used qualitative environmental criteriaand five evaluation criteria were determined to evaluate


Figure 2 Distribution of the local suppliers

Greenproducts

Pollutioncontrol

Environmentalmanagement

system

Environmentalcollaboration

Environmentalcompetency

Figure 3 ANP hierarchy for the green supplier evaluation

environmental performance of suppliers These are environ-mental technologies and pollution control (PC) environ-mental management system (EMS) green products (GP)environmental collaboration (ECO) environmental compe-tency (EC)

4 Application

41 Application of the Proposed Supplier Evaluation Method-ology The application was performed in the company whichis a multinational company and one of the most importantand biggest pioneer companies in the Turkish automobileindustry The company implements green practices at allstages of the manufacturing process The company workswith more than 60 local suppliers performing in TurkeyDistribution of the local suppliers of the company can be seenin Figure 2

42 The Computational Steps of the ProposedIntegrated Framework

Step 1 (constructing ANP decision model) ANP decisionmodel was constructed based on opinions of five experts

working in the companyThis model is presented in Figure 3The model consists of five main factors environmental com-petency environmental collaboration environmental man-agement system green products and environmental tech-nologies and pollution control Environmental competencycontains four sub-factors (EC1 EC4) environmentalcollaboration contains four sub-factors (ECO1 ECO4)environmental management system contains two sub-factors(EMS1 EMS2) green products contains three sub-factors(GP1 GP3) and environmental technologies and pollu-tion control contains four sub-factors (PC1 PC4) Thesecriteria are shown in Table 2

Step 2 (pairwise comparisons) The pairwise comparisons(cluster comparisons and element comparisons) were per-formed using the 9-point scale of Saaty [17] where 1 3 57 and 9 indicate equal importance moderate importancestrong importance very strong importance and extremeimportance respectively 2 4 6 and 8 are used for compro-mise between the above values The ANP model is solvedusing ldquoSuper Decisionsrdquo software All inconsistency ratios arebelow 01 which indicates acceptable levels of consistencyacross pairwise comparisons

Step 3 (constructing supermatrix) In this step the unweight-ed supermatrix weighted supermatrix and limit supermatrixwere constructed The unweighted supermatrix was calcu-lated with priority vectors obtained from pairwise compar-ison matrices for interdependencies among the sub-factorsThe unweighted supermatrix cannot reflect the normalizedweights as the sum of the column values is not equal to1 Accordingly the unweighted matrix was transformed tothe weighted supermatrix to reveal influences on a 0-1 scaleThe weighted supermatrix is presented in Table 3 Finally thelimit matrix was obtained by means of increasing the powerof the weighted supermatrix The limit matrix is presented inTable 4

Step 4 (cetermining weights of criteria) Weights of criteriato be used in TOPSIS method are determined based on thelimit matrix as shown in Table 4


Table4Limitsuperm

atrix

EC1

EC2

EC3

EC4

ECO1

ECO2

ECO3

ECO4

EMS1

EMS2

GP1

GP2

GP3

PC1

PC2

PC3

PC4

EC1

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

EC2

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

EC3

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

EC4

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

ECO1

00364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

5EC

O2

00246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

8EC

O3

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

ECO4

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

EMS1

00744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

1EM

S2004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

GP1

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

GP2

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

GP3

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

PC1

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

PC2

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

PC3

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

PC4

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988


Table 5 Standard decision matrix

Supplier Pollution controlEnvironmentmanagementsystem

Green products Environmental collaboration Environmental competency

pc1 pc2 pc3 pc4 ems1 ems2 gp1 gp2 gp3 eco1 eco2 eco3 eco4 ec1 ec2 ec3 ec4S1 633 500 667 600 600 467 633 500 533 567 633 433 567 533 633 567 567S2 475 450 525 625 400 500 575 400 550 475 425 425 450 425 625 525 450S3 533 467 567 567 567 533 533 433 500 567 567 433 533 567 633 567 533S4 533 567 467 533 500 500 633 500 633 467 600 400 467 467 500 533 433S5 550 550 500 525 500 500 600 625 600 500 625 375 500 500 550 525 500S6 680 560 620 620 600 600 640 560 540 560 600 580 620 600 620 620 540S7 500 333 400 433 300 567 400 567 367 433 367 400 400 400 433 367 333S8 575 575 525 500 525 600 575 575 600 600 575 475 625 525 550 550 600S9 600 450 500 450 350 525 475 500 425 425 600 500 500 575 525 475 550S10 640 480 640 620 600 540 580 540 580 580 560 480 500 540 580 600 560S11 567 567 533 667 533 633 633 600 633 600 600 467 600 433 633 567 567S12 540 480 580 520 540 500 600 500 600 500 460 460 520 460 580 580 500S13 433 333 567 600 400 433 567 533 533 433 333 367 400 400 600 500 400S14 575 475 625 575 600 550 550 575 575 575 550 350 525 475 625 600 600S15 625 475 600 425 650 550 575 375 550 550 525 500 600 550 600 600 475S16 533 433 567 467 467 433 600 567 533 433 367 367 433 333 567 533 533S17 650 500 600 550 650 550 600 600 500 400 650 300 600 600 500 650 650S18 667 533 633 633 633 567 633 500 567 567 633 567 533 533 567 600 533

Step 5 (construction of the standard decision matrix) Forthis first alternatives were determined We aimed to evalu-ate environmental performance of suppliers manufacturingchassis and its components The company has 18 suppliersmanufacturing chassis and its components Suppliers wereevaluated using a 1ndash7 scale (1-lowest performance 7-highest performance) by five decision makers working inpurchasing (2 members) quality (2 members) and man-ufacturing (1 member) departments and mean values foreach suppliers were calculated Than initial decision matrixfor TOPSIS was constructed based on these mean values aspresented in Table 5

Step 6 (construct the normalized decision matrix) In thisstep the normalized decision matrix 119877 = [119903

119894119895] is calculated

The normalized value 119903119894119895is calculated

119903119894119895=119891119894119895

radicsum119899

119895=11198912119894119895

(1)

where 119895 = 1 119899 119894 = 1 119898 Normalized decisionmatrix for the evaluation of green supplier performance(GSP) problem is shown in Table 6

Step 7 (construction of the weighted standard decisionmatrix) The weighted normalized decision matrix is cal-culated by multiplying the normalized decision matrix byits associated weights The weighted normalized value V

119894119895is

calculated from (2) Here 119908119894119895represents the weight of the 119895th

attribute or criterion The Weighted normalized matrix forthe GSP evaluation problem is shown in Table 7

V119894119895= 119908119894119895119903119894119895 (2)

Step 8 (construction of ideal positive (119881+) and ideal negative(119881minus) solutions) The positive ideal solutions (119881+) and nega-tive ideal solutions (119881minus) are determined as follows119881+= V+

119894 V

+

119899 = (Max V

119894119895| 119895 isin 119869) (Min V

119894119895| 119895 isin 119869

1015840)

(3)

119881minus= Vminus

119894 V

minus

119899 = (Min V

119894119895| 119895 isin 119869) (Max V

119894119895| 119895 isin 119869

1015840)

(4)

where 119881+ is associated with the positive criteria and 119881minus isassociated with the negative criteria PIS and NIS for the GSPevaluation problem are presented in Table 7

Step 9 (calculation of separation measures and relative close-ness to ideal solution) The separation measures are cal-culated using the 119898-dimensional Euclidean distance Theseparation measure 119878+

119894of each alternative and the separation

measure 119878minus119894of each alternative are calculated respectively as

follows

119878+

119894= radic

119899

sum119895=1

(V119894119895minus V+119895)2

119894 = 1 119898 (5)

119878minus

119894= radic

119899

sum119895=1

(V119894119895minus Vminus119895)2

119894 = 1 119898 (6)


Table 6 Normalized decision matrix of TOPSIS




The relative closeness to the ideal solution is calculatedfrom (7) and then alternatives are ranked in descending orderwhere the index value of 119862

119894lies between 0 and 1 The larger

the index value the better the performance of the alternatives

119862119894=119878minus119894

119878+119894+ 119878minus119894

(7)

Separation measures (119878+119894and 119878minus

119894) and relative closeness

to ideal solution (119862119894) for GSP evaluation problem are shown

in Table 8 Then classes of the suppliers (A B C D) weredetermined according to the scale presented in Table 9

Four of the suppliers are at ldquoArdquo class and their environ-mental performance are perfect Seven of the 18 evaluatedfirms are at ldquoBrdquo class Their environmental performances aregood But in order to have better performance they shoulddevelop their environmental issues one of the suppliers areat ldquoCrdquo class Their environmental performance is inade-quate and needs improvement They perform some activitiesrelated with environment Five of the suppliers are at ldquoDrdquoclass Their environmental performance is so bad They needto improve and develop their environmental performancevery urgently in order to do business with their customers

5 Conclusions

Theneed to continuously improve the corporate performancewill force firms to select and evaluate their suppliers accord-ing to their environmental performance and involve alsosuppliers in their environmental programs Thus companies

emphasizes the importance ofmethodologieswhich allow thepurchasing team to select only environmentally efficient sup-pliers In order to develop their environmental performancefirms need to work together with the suppliers which havehigh environmental performance and they have towork theirsuppliers cooperatively

This paper presents a framework of environmental cri-teria that a company can consider during their supplierselection process This study proposes a hybrid MCDMapproach to evaluate performance of green suppliers becausethere is an increasing need to develop GSCM practices Aftera comprehensive literature research andwith the validation ofindustrial experts possible green supplier evaluation criteriawere defined and an evaluation model was developed Theproposed model was applied in an automobile companywhich is one of the best companies considering environ-mental issues in Turkey In this study 18 suppliers of thecompany that are manufacturing chassis and componentswere evaluated by a model that integrates ANP and TOPSISinto the context of green performance Furthermore TOPSISmethod was used to sequence the suppliers for ideal solutionof this problem efficiently

Also this study has some limitations One of the limi-tations of the study is that we use only qualitative factorsto evaluate suppliersrsquo environmental performance In futurestudies evaluation criteria should be expanded includingqualitative environmental factors for example carbon foot-print and quantity of emissions and so forth

This research suggests further studies in order to extendthe scope of this study This study can be extended to


Table 7 Weighted matrix



pc1 pc2 pc3 pc4 ems1 ems2 gp1 gp2 gp3 eco1 eco2 eco3 eco4 ec1 ec2 ec3 ec4S1 0038 0072 0049 0059 0017 0030 0016 0022 0097 0058 0159 0018 0160 0076 0081 0071 0096S2 0042 0050 0087 0043 0044 0018 0016 0022 0068 0051 0199 0011 0143 0076 0066 0080 0085S3 0024 0041 0054 0047 0020 0021 0013 0014 0073 0036 0089 0010 0090 0049 0064 0068 0054S4 0032 0045 0028 0017 0017 0019 0008 0018 0049 0023 0124 0006 0063 0061 0030 0050 0048S5 0030 0044 0063 0038 0040 0023 0012 0017 0060 0051 0159 0011 0127 0086 0066 0080 0076S6 0030 0065 0043 0034 0031 0021 0016 0022 0097 0035 0178 0009 0097 0059 0041 0071 0050S7 0017 0027 0071 0043 0017 0015 0013 0017 0077 0026 0055 0006 0049 0019 0053 0062 0050S8 0047 0044 0087 0053 0040 0021 0018 0040 0087 0051 0178 0018 0127 0076 0059 0080 0076S9 0042 0065 0071 0043 0055 0030 0018 0022 0077 0035 0178 0012 0160 0097 0047 0110 0096S10 0019 0041 0065 0033 0020 0019 0015 0038 0087 0040 0100 0007 0055 0028 0055 0075 0073S11 0032 0061 0049 0033 0031 0021 0015 0035 0087 0040 0193 0008 0111 0067 0050 0068 0067S12 0049 0063 0075 0046 0044 0030 0017 0028 0070 0050 0178 0019 0171 0097 0063 0095 0078S13 0026 0022 0031 0022 0011 0026 0006 0029 0032 0030 0067 0009 0071 0043 0031 0033 0030S14 0035 0066 0054 0030 0034 0030 0013 0030 0087 0058 0164 0013 0174 0074 0050 0075 0096S15 0042 0057 0079 0038 0049 0030 0009 0020 0060 0064 0178 0009 0127 0086 0066 0100 0118S16 0038 0041 0049 0024 0015 0023 0009 0022 0043 0029 0178 0014 0111 0089 0046 0056 0080S17 0043 0046 0080 0046 0044 0024 0014 0026 0081 0054 0155 0013 0111 0078 0056 0089 0083S18 0035 0066 0059 0033 0025 0012 0012 0030 0066 0036 0178 0010 0123 0097 0050 0068 0054119881+ 0042 0050 0087 0043 0044 0018 0016 0022 0068 0051 0199 0011 0143 0076 0066 0080 0085119881minus 0024 0041 0054 0047 0020 0021 0013 0014 0073 0036 0089 0010 0090 0049 0064 0068 0054

Table 8 Environmental performance of suppliers

Suppliers 119878minus

119894119878+

119894119862119894

Ranking ClassS1 002296 000382 085747 6 BS2 001670 000297 084877 7 BS3 001376 001685 044958 14 DS4 000961 002152 030866 16 DS5 002790 000572 082987 9 BS6 002233 001026 068508 13 CS7 000835 002886 022442 17 DS8 003235 000385 089367 5 BS9 004175 000223 094931 2 AS10 001293 001889 040646 15 DS11 002717 000712 079237 10 BS12 004153 000206 095268 1 AS13 000535 003106 014704 18 DS14 003673 000366 090931 4 AS15 003815 000290 092946 3 AS16 002451 000994 071145 12 CS17 002824 000504 084861 8 BS18 002756 000734 078955 11 B

other industries Evaluation criteria can be changed fromone sector to an other Appropriate evaluation criteria ofgreen performance should be selected according to the sector

Table 9 Classification scale

119862 Class Definition0900ndash1000 A Environmental performance is perfect0700ndash0899 B Environmental performance is good

0500ndash0699 C Environmental performance is inadequateIt needs improvements

0000ndash0499 D Environmental performance is bad It has tobe certainly developed

Therefore the green supply chain that is already a hot topiccould become the new trend of the future

References

[1] A H I Lee H Y Kang C F Hsu and H C Hung ldquoA greensupplier selectionmodel for high-tech industryrdquo Expert Systemswith Applications vol 36 pp 7917ndash7927 2009

[2] R J Kuo Y C Wang and F C Tien ldquoIntegration of artificialneural network and MADA methods for green supplier selec-tionrdquo Journal of Cleaner Production vol 18 no 12 pp 1161ndash11702010

[3] S Vachon and R D Klassen ldquoGreen project partnership in thesupply chain the case of the package printing industryrdquo Journalof Cleaner Production vol 14 no 6-7 pp 661ndash671 2006


[4] G Noci ldquoDesigning ldquogreenrdquo vendor rating systems for theassessment of a supplierrsquos environmental performancerdquo Euro-pean Journal of Purchasing and Supply Management vol 3 no2 pp 103ndash114 1997

[5] G Buyukozkan andG Ciftci ldquoA novel hybridMCDMapproachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012

[6] D G Li Z Y Zhou andC Yang ldquoAmodel on supplier selectionin Green Supply chain based on HP Neural networkrdquo AppliedMechanics and Materials vol 143-144 pp 312ndash327 2012

[7] R Handfield S V Walton R Sroufe and S A Melnyk ldquoApply-ing environmental criteria to supplier assessment a study inthe application of the analytical hierarchy processrdquo EuropeanJournal of Operational Research vol 141 no 1 pp 70ndash87 2002

[8] L Y Y Lu C H Wu and T C Kuo ldquoEnvironmental principlesapplicable to green supplier evaluation by using multi-objectivedecision analysisrdquo International Journal of Production Researchvol 45 no 18-19 pp 4317ndash4331 2007

[9] P Rao and D Holt ldquoDo green supply chains lead to competi-tiveness and economic performancerdquo International Journal ofOperations and ProductionManagement vol 25 no 9 pp 898ndash916 2005

[10] G Tuzkaya A Ozgen D Ozgen and U R Tuzkaya ldquoEnvi-ronmental performance evaluation of suppliers a hybrid fuzzymulti-criteria decision approachrdquo International Journal of Envi-ronmental Science and Technology vol 6 no 3 pp 477ndash4902009

[11] W H Tsai and S J Hung ldquoA fuzzy goal programming approachfor green supply chain optimisation under activity-based cost-ing and performance evaluation with a value-chain structurerdquoInternational Journal of Production Research vol 47 no 18 pp4991ndash5017 2009

[12] C Bai and J Sarkis ldquoGreen supplier development analyticalevaluation using rough set theoryrdquo Journal of Cleaner Produc-tion vol 18 no 12 pp 1200ndash1210 2010

[13] A Awasthi S S Chauhan and S K Goyal ldquoA fuzzy multi-criteria approach for evaluating environmental performance ofsuppliersrdquo International Journal of Production Economics vol126 no 2 pp 370ndash378 2010

[14] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012

[15] V Baskaran S Nachiappan and S Rahman ldquoIndian textilesuppliersrsquo sustainability evaluation using the grey approachrdquoInternational Journal of Production Economics vol 135 no 2pp 647ndash658 2012

[16] K Shaw R Shankar S S Yadav and L S Thakur ldquoSupplierselection using fuzzy AHP and fuzzy multi-objective linearprogramming for developing low carbon supply chainrdquo ExpertSystems with Applications vol 39 pp 8182ndash8192 2012

[17] T L Saaty Decision Making with Dependence and FeedbackTheAnalytic Network Process RWSPublications Pittsburgh PaUSA 2nd edition 2001

[18] K Green B Morton and S New ldquoPurchasing and environ-mental management interaction policies and opportunitiesrdquoBusiness Strategy and the Environment vol 5 pp 188ndash197 1996

[19] S K Srivastava ldquoGreen supply-chain management a state-of-the-art literature reviewrdquo International Journal of ManagementReviews vol 9 no 1 pp 53ndash80 2007

[20] E U Olugu K Y Wong and A M Shaharoun ldquoDevelopmentof key performance measures for the automobile green supplychainrdquo Resources Conservation and Recycling vol 55 no 6 pp567ndash579 2011

[21] A A Hervani M M Helms and J Sarkis ldquoPerformance mea-surement for green supply chain managementrdquo Benchmarkingvol 12 no 4 pp 330ndash353 2005

[22] B Rettab and A Ben Brik Green Supply Chain in Dubai DubaiChamber Centre for Responsible Business Dubai Dubai UAE2008

[23] R Narasimhan and J R Carter Environmental Supply ChainManagement The Center for Advanced Purchasing StudiesArizona State University Tempe Ariz USA 1998

[24] J D Linton R Klassen and V Jayaraman ldquoSustainable supplychains an introductionrdquo Journal of Operations Managementvol 25 no 1 pp 1075ndash1082 2007

[25] R Handfield R Sroufe and S Walton ldquoIntegrating envi-ronmental management and supply chain strategiesrdquo BusinessStrategy and the Environment vol 14 no 1 pp 1ndash19 2005

[26] J Hall ldquoEnvironmental supply chain dynamicsrdquo Journal ofCleaner Production vol 8 no 6 pp 455ndash471 2000

[27] Q Zhu J Sarkis and K-H Lai ldquoConfirmation of a mea-surement model for green supply chain management prac-tices implementationrdquo International Journal of Production Eco-nomics vol 111 no 2 pp 261ndash273 2008

[28] T Wu D Shunk J Blackhurst and R Appalla ldquoAIDEA amethodology for supplier evaluation and selection in a supplier-based manufacturing environmentrdquo International Journal ofManufacturing Technology and Management vol 11 no 2 pp174ndash192 2007

[29] S R Gordon ldquoSupplier evaluation benefits barriers and bestpracticesrdquo in Proceedings of the 91st Annual International SupplyManagement Conference May 2006

[30] P K Humpreys Y K Wong and F T S Chan ldquoIntegratingenvironmental criteria into the supplier selection processrdquoJournal ofMaterials Processing Technology vol 138 pp 349ndash3562003

[31] P Humphreys R McIvor and F Chan ldquoUsing case-basedreasoning to evaluate supplier environmental managementperformancerdquo Expert Systems with Applications vol 25 no 2pp 141ndash153 2003

[32] C W Hsu and A H Hu ldquoApplying hazardous substance man-agement to supplier selection using analytic network processrdquoJournal of Cleaner Production vol 17 pp 255ndash264 2009

[33] T L Saaty ldquoDecision makingmdashthe analytic hierarchy andnetwork processes (AHPANP)rdquo Journal of Systems Science andSystems Engineering vol 13 no 1 pp 1ndash34 2004

[34] W H Tsai and W C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009

[35] C L Lin M S Hsieh and G H Tzeng ldquoEvaluating vehicletelematics system by using a novel MCDM techniques withdependence and feedbackrdquo Expert Systems with Applicationsvol 7 no 10 pp 6723ndash6736 2010

[36] E Manokaran S Subhashini S Senthilvel R Muruganand-ham and K Ravichandran ldquoApplication of multi criteria deci-sion making tools and validation with optimization technique-case study using TOPSIS ANN amp SAWrdquo International Journalof Management amp Business Studies vol 1 no 3 pp 112ndash115 2011


[37] M T Chu J Shyu G H Tzeng and R Khosla ldquoComparisonamong three analytical methods for knowledge communitiesgroup-decision analysisrdquo Expert Systems with Applications vol33 no 4 pp 1011ndash1024 2007

[38] G R Jahanshahloo F H Lotfi andM Izadikhah ldquoAn algorith-mic method to extend TOPSIS for decision-making problemswith interval datardquo Applied Mathematics and Computation vol175 no 2 pp 1375ndash1384 2006

[39] E Oz and F O Baykoc ldquoTedarikci secimi problemine kararteorisi destekli uzman sistem yaklasımırdquo Journal of the Facultyof Engineering and Architecture of Gazi University vol 19 no 3pp 275ndash286 2004

[40] A G Abdul-Mumin ldquoInstrumental and interpersonal determi-nants of relationship satisfaction and commitment in industrialmarketsrdquo Journal of Business Research vol 58 pp 619ndash6282005

[41] L Shenc L Olfat K Govindan R Khodaverdia and A DiabatldquoA fuzzy multi criteria approach for evaluating green supplierrsquosperformance in green supply chain with linguistic preferencesrdquoResources Conservation and Recycling 2012

[42] G Azzone and G Noci ldquoMeasuring the environmental perfor-mance of new products an integrated approachrdquo InternationalJournal of Production Research vol 3 no 11 pp 3055ndash30781996

[43] Q Zhu and J Sarkis ldquoRelationships between operationalpractices and performance among early adopters of greensupply chain management practices in Chinese manufacturingenterprisesrdquo Journal of Operations Management vol 22 no 3pp 265ndash289 2004

International Journal of

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Active and Passive Electronic Components

Control Scienceand Engineering

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Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design



Shock and Vibration


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Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014


Chemical EngineeringInternational Journal of Antennas and

Propagation




Navigation and Observation



DistributedSensor Networks



Therefore this study was performed in the area of green sup-plier performance Our contributions from this study include(1) modeling the decision problem within the context of aGSCM decision and (2) evaluation of supplier performanceby the view point of environmental issues

In the green supply chain literature various techniquesare used to evaluate and select green suppliers such as ratingsystem [4] analytic hierarchy process (AHP) [7] fuzzy AHP[8 9] a hybrid fuzzy analytic network process (ANP) andfuzzy Preference Ranking Organization method for enrich-ment evaluations (PROTMETHEE) [10] fuzzy extendedAHP [1] fuzzy goal programming [11] artificial neuralnetwork data envelopment analysis and analytic netwokprocess (ANP) [2] Rough set theory [12] fuzzy Techniquefor Order Preference by similarity to ideal solution (TOPSIS)[13] an integrated model of fuzzy decision making trial andevaluation laboratory (DEMATEL) ANP TOPSIS [5] a grey-based DEMATEL approach [14] Grey approach [15] fuzzyAHP and fuzzy multiobjective linear programming [16]

Because there are both qualitative and quantitative factorsthat influence the evaluation and selection of green suppliersevaluation and selection problem of green supplier is a multi-criteria decision making (MCDM) problem Thus there is aneed to employ MCDM techniques to tackle green supplierselection problem appropriately Firstly ANP technique [17]is applied to handle the relationships and dependence of se-lection criteria and subcriteria and to determine weightsof criteria Then TOPSIS technique is used to sequencethe suppliers for ideal solution of the supplier evaluationproblem

The paper is organized as follows The paper beginswith the literature research about GSCM Then after abrief literature review of methodologies used evaluation ofsupplierrsquos environmental performance and selection of greensupplier are examined to develop a structure for evaluatinggreen supplier performance and selecting green suppliersThe next section illustrates the proposed green supplierevaluation and selection methodology through the case ofan automobile company in Turkey The paper finishes by adiscussion section

2 Literature Review

21 Green Supply Chain Green et al [18] defined greensupply as ldquothe way in which innovations in SCM andindustrial purchasing may be considered in the context ofthe environmentrdquo Srivastava [19] defined GSCM as ldquointegrat-ing environmental thinking into supply chain managementincluding product design material sourcing and selectionmanufacturing processes delivery of the final product to theconsumers and end-of-life management of the product afterits useful liferdquo Also many researchers have defined a GSCMin various manners using different terms [20] GSCM can bedefined as integrating environmental issues into supply chainmanagement Originally GSCM was bounded to purchasingissues Hervani et al [21] defined GSCM as integratingsuppliers into environmental management processes Rettaband Ben Brik [22] defined the GSC as a managerial approachthat seeks to minimize a product or servicersquos environmental

effect The bottom line of these definitions is the same thatis ldquoenvironmentrdquo GSCM contains the activities such as wastereduction recycling reuse and the substitution of materials[23] and it includes green purchasing green manufacturingandmaterialmanagement green distribution andmarketingand reverse logistics [24]

According to Narasimhan and Carter [23] GSCMincludes ldquothe purchasing functionrsquos involvement in activitiesthat include reduction recycling reuse and the substitutionof materialsrdquoThemost common GSCM practices are to eval-uate the environmental performance of suppliers to requiresuppliers to acceptmeasures providing environmental qualityof their supplied products and to evaluate the cost of waste intheirmanufacturing processes [7] However GSCMpracticesalso extend to the entire value chain (from supplier toconsumer) when organizations inform buyers of ways toreduce their impacts on the natural environment [25]

Hall [26] investigated the circumstances under whichldquoenvironmental supply chain dynamicsrdquo emerge He arguedthat environmental supply chain dynamics emerge whenenvironmental pressures are synthesized with supply chainpressures which have had considerable influence on thesupply base on the strength of case studies in the Britishand Japanese food retail sector and the British aerospaceindustry Zhu et al [27] expressed that ldquorange of GSCMchanges from green purchasing (GP) to integrated life-cyclemanagement supply chains flowing from supplier throughto manufacturer customer and closing the loop with reverselogisticsrdquo

According to Vachon and Klassen [3] suppliers manu-facturers and customers should collaborate to reduce haz-ardous environmental effects from manufacturing processesand products

22 Evaluation of Green Supplier Performance Supplier eval-uation process is an important element in supplier-basedmanufacturing and SCM has been gaining attention inboth the academic literature and industrial practice Thesupplier selection decision is one of the critical and importantissues in SCM for many organizations to help maintain astrategically competitive position [28] It becomes one of themost important components of production and operationsmanagement for many organizations Supplier selection andevaluation process is the process by which the companyidentifies evaluates and contracts suppliers

Measuring and understanding supplier performance iscrucial to provide a well-functioning supply chain and todevelop competitive position of a company The goal of thesupplier evaluation is to develop the performance of keysuppliers [29] Companies have some advantages throughevaluating their suppliers They have better visibility intosupplier performance decrease risk reduce order cycle timesand inventory and thus increase competitive advantage andcoordinate practices between themselves and their suppliers[29]

In the last two decades there is increasing attentionto evaluate suppliersrsquo green performance There are lotsof studies related this topics in the literature A detailedliterature search was performed about the concepts of GSC


ble1Cr

iteria

used

toevaluategreensupp

liers

Author(s)

Azzon

eand

Noci1996

[42]

Noci1997

[4]

Hum

preyse

tal2003

[30]

Zhuand

Sarkis

2004

[43]

Hum

phreys

etal

2003

[31]

Tuzkayae

tal

2009

[10]

Leee

tal

2009

[1]

Kuoetal

2010

[2]

Baiand

Sarkis

2010

[12]

Fuetal

2012

[14]

Buyuko

zkan

andCiftc

i2012

[5]

Evaluatio

ncriteria


environm

en-

tal

effectiv

eness

(ii)E

nviro

n-mental

efficiency

(iii)ldquoG

reenrdquo

image

(iv)E

nviro

n-mental

flexibility

(i)Green

competencies

(ii)C

urrent

environm

en-

talefficiency

(iii)Supp

lierrsquos

greenim

age

(iv)N

etlife

cycle

cost

(i)En

viron-

mental

competen-

cies

(ii)M

anage-

ment

decisio

ns(iii)Green

image

(iv)D

esign

for

environm

ent

(v)E

nviro

n-mental

managem

ent

syste

m

(i)Internal

environm

ental

managem

ent

(ii)ISO

14001

certificatio

n(iii)Ex

ternal

GSC

Mpractic

es(iv

)Investm

ent

recovery

(v)E

codesig

n

(i)En

vironm

ental

costs

(pollutant

effects)

(ii)E

nviro

nmental

costs

(improvem

ent)

(iii)Managem

ent

competencies

(iv)G

reen

image

(v)D

esignfor

environm

ent

(vi)En

vironm

ental

managem

ent

syste

ms

(vii)

Environm

ental

competencies

(i)Po

llutio

ncontrol

(ii)G

reen

process

managem

ent

(iii)En

viron-

mentaland

legisla

tive

managem

ent

(iv)E

nviro

n-mentalcosts

(v)G

reen

prod

uct

(vi)Green

image

(i)Quality

(ii)T

echn

o-logical

capability

(iii)To

tal

prod

uctlife

cycle

cost

(iv)G

reen

image

(v)P

ollutio

ncontrol

(vi)En

viron-

mental

managem

ent

(vii)

Green

prod

uct

(viii)G

reen

competence

(i)Quality

(ii)C

ost

(iii)Delivery

(iv)S

ervice

(v)C

orpo

rate

social

respon

sibility

(vi)

Environm

ent

(i)Green

know

ledge

transfe

rand

commun

ication

(ii)Investm

ent

andkn

owledge

transfe

r(iii)Managem

ent

and

organizatio

nal

practic

es

(i)Green

know

ledge

transfe

rand

commun

i-catio

n(ii)Invest-

mentand

resource

transfe

r(iii)Man-

agem

ent

andorga-

nizatio

nal

practic

es

(i)Organization

(ii)F

inancial

perfo

rmance

(iii)Service

quality

(iv)T

echn

olog

y(v)G

reen

competencies

Focuso

fthes

tudy

Evaluatethe

environm

en-

tal

perfo

rmance

ofa

companyrsquos

existing

operation

syste

m

Evaluate

supp

liersrsquo

environm

en-

tal

perfo

rmance

Evaluatio

nof

supp

lier

perfo

rmance

andenviron-

mental

issues

Evaluatesupp

liersrsquo

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ental

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rmance

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nof

supp

liers

environm

ental

perfo

rmance

Selectingof

green

supp

liers

Evaluatin

ggreen

supp

lier

developm

ent

programsfor

organizatio

ns

Indu

stry

An

illustrative

exam

ple

An

illustrative

exam

ple

An

illustrative

exam

ple

Anillustrative

exam

ple

Whitegood

smanufacturer

Turkey

LTF-LC

Dindu

stry

Taiwan

Electro

nic

company

Taiwan

Anillustrative

exam

ple

Telecom-

mun

ica-

tions

equipm

ent

provider

China

Automotive

indu

stry

Turkey

Evaluatio

nmetho

ds

Com

paris

onof

some

techniqu

essuch

asAHP

scoring

metho

dsand

DCF

techniqu

es

Know

ledge-

based

syste

m

Know

ledge-based

syste

ms(KB

S)and

case-based

reason

ing(C

BR)

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analysis(M

AA)

ahybrid

fuzzy

analytic

network

processa

ndfuzzy

PROMET

HEE

Delp

himetho

dand

thefuzzy

extend

edAHP

Data

envelopm

ent

analysis

(DEA

)and

ANP

Roug

hsettheory



Criteria Definition

EC1



























atrix

EC1

EC2

EC3

EC4

ECO1

ECO2

ECO3

ECO4

EMS1

EMS2

GP1

GP2

GP3

PC1

PC2

PC3

PC4

EC1

001387

001387

001387

001387

001994

012282

012500

005714

001556

00546

0002138

000000

001866

01046

00119

69000822

000000

EC2

010117

010117

010117

010117

006904

001104

002500

002857

002496

002830

006

413

007150

006001

000000

003512

004946

007753

EC3

005676

005676

005676

005676

003701

002535

002500

005714

009837

006

018

006

413

021451

006

001

003168

002275

008671

007753

EC4

002205

002205

002205

002205

007401

004

078

002500

005714

006111

005693

002138

007150

003233

005756

001628

004946

003877

ECO1

000796

004

658

004321

003594

005576

006154

002942

003630

007797

009063

001658

000000

003487

001084

000823

004

254

003527

ECO2

003893

000583

000825

001328

009425

006153

010975

0114

21003047

002483

001190

000

000

001162

003463

003662

000826

000720

ECO3

001430

000

604

000825

000

446

001112

001539

002912

001084

001359

002013

002036

000

000

001162

001295

002240

000522

001208

ECO4

001430

001702

001578

002180

003887

006154

003171

003865

007797

006

441

002091

000000

001162

001706

000823

001944

002092

EMS1

003774

005661

006

469

005032

010000

013333

00500

0013333

006

667

006

667

014461

000

000

007231

003774

002516

005661

005661

EMS2

003774

001887

001078

002516

01000

0006

667

01500

0006

667

013333

013333

000

000

000

000

007231

003774

005032

001887

001887

GP1

016380

016380

017677

010920

006

667

01000

0013333

01000

001000

0000

000

020123

042071

014184

016380

010920

016380

024571

GP2

000

000

000

000

009729

000

000

000

000

000

000

000

000

000

000

000

000

000

000

002930

006125

002364

000

000

000

000

000

000

000

000

GP3

016380

016380

005354

021840

013333

010000

006

667

010000

010000

020000

007679

016053

014184

016380

021840

016380

008190

PC1

015120

000

000

003474

008869

004541

008571

006756

010316

004

488

010924

003273

000

000

002723

014480

014480

014480

014480

PC2

015120

002907

00260

6003948

00244

7008571

009580

003788

001315

004

646

008036

000

000

013327

001958

001958

001958

001958

PC3

002520

018315

017923

013699

008472

001429

001421

003788

010939

001675

005693

000

000

007341

006516

006516

006516

006516

PC4

000000

011538

008757

006245

004541

001429

002243

002108

003258

002755

013729

000000

007341

009806

009806

009806

009806














ANP

TOPSIS
















Greenproducts

Pollutioncontrol


system





4 Application









Table4Limitsuperm

atrix

EC1

EC2

EC3

EC4

ECO1

ECO2

ECO3

ECO4

EMS1

EMS2

GP1

GP2

GP3

PC1

PC2

PC3

PC4

EC1

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

EC2

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

EC3

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

EC4

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

ECO1

00364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

5EC

O2

00246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

8EC

O3

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

ECO4

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

EMS1

00744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

1EM

S2004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

GP1

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

GP2

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

GP3

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

PC1

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

PC2

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

PC3

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

PC4

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988










119903119894119895=119891119894119895

radicsum119899

119895=11198912119894119895

(1)



119894119895is



V119894119895= 119908119894119895119903119894119895 (2)


119894 V

+

119899 = (Max V

119894119895| 119895 isin 119869) (Min V

119894119895| 119895 isin 119869

1015840)

(3)

119881minus= Vminus

119894 V

minus

119899 = (Min V

119894119895| 119895 isin 119869) (Max V

119894119895| 119895 isin 119869

1015840)

(4)





follows

119878+

119894= radic

119899

sum119895=1

(V119894119895minus V+119895)2

119894 = 1 119898 (5)

119878minus

119894= radic

119899

sum119895=1

(V119894119895minus Vminus119895)2

119894 = 1 119898 (6)









119862119894=119878minus119894

119878+119894+ 119878minus119894

(7)






5 Conclusions













119894119878+

119894119862119894








References
















































RoboticsJournal of





Journal of



RotatingMachinery





VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation










ble1Cr

iteria

used

toevaluategreensupp

liers

Author(s)

Azzon

eand

Noci1996

[42]

Noci1997

[4]

Hum

preyse

tal2003

[30]

Zhuand

Sarkis

2004

[43]

Hum

phreys

etal

2003

[31]

Tuzkayae

tal

2009

[10]

Leee

tal

2009

[1]

Kuoetal

2010

[2]

Baiand

Sarkis

2010

[12]

Fuetal

2012

[14]

Buyuko

zkan

andCiftc

i2012

[5]

Evaluatio

ncriteria


environm

en-

tal

effectiv

eness

(ii)E

nviro

n-mental

efficiency

(iii)ldquoG

reenrdquo

image

(iv)E

nviro

n-mental

flexibility

(i)Green

competencies

(ii)C

urrent

environm

en-

talefficiency

(iii)Supp

lierrsquos

greenim

age

(iv)N

etlife

cycle

cost

(i)En

viron-

mental

competen-

cies

(ii)M

anage-

ment

decisio

ns(iii)Green

image

(iv)D

esign

for

environm

ent

(v)E

nviro

n-mental

managem

ent

syste

m

(i)Internal

environm

ental

managem

ent

(ii)ISO

14001

certificatio

n(iii)Ex

ternal

GSC

Mpractic

es(iv

)Investm

ent

recovery

(v)E

codesig

n

(i)En

vironm

ental

costs

(pollutant

effects)

(ii)E

nviro

nmental

costs

(improvem

ent)

(iii)Managem

ent

competencies

(iv)G

reen

image

(v)D

esignfor

environm

ent

(vi)En

vironm

ental

managem

ent

syste

ms

(vii)

Environm

ental

competencies

(i)Po

llutio

ncontrol

(ii)G

reen

process

managem

ent

(iii)En

viron-

mentaland

legisla

tive

managem

ent

(iv)E

nviro

n-mentalcosts

(v)G

reen

prod

uct

(vi)Green

image

(i)Quality

(ii)T

echn

o-logical

capability

(iii)To

tal

prod

uctlife

cycle

cost

(iv)G

reen

image

(v)P

ollutio

ncontrol

(vi)En

viron-

mental

managem

ent

(vii)

Green

prod

uct

(viii)G

reen

competence

(i)Quality

(ii)C

ost

(iii)Delivery

(iv)S

ervice

(v)C

orpo

rate

social

respon

sibility

(vi)

Environm

ent

(i)Green

know

ledge

transfe

rand

commun

ication

(ii)Investm

ent

andkn

owledge

transfe

r(iii)Managem

ent

and

organizatio

nal

practic

es

(i)Green

know

ledge

transfe

rand

commun

i-catio

n(ii)Invest-

mentand

resource

transfe

r(iii)Man-

agem

ent

andorga-

nizatio

nal

practic

es

(i)Organization

(ii)F

inancial

perfo

rmance

(iii)Service

quality

(iv)T

echn

olog

y(v)G

reen

competencies

Focuso

fthes

tudy

Evaluatethe

environm

en-

tal

perfo

rmance

ofa

companyrsquos

existing

operation

syste

m

Evaluate

supp

liersrsquo

environm

en-

tal

perfo

rmance

Evaluatio

nof

supp

lier

perfo

rmance

andenviron-

mental

issues

Evaluatesupp

liersrsquo

environm

ental

perfo

rmance

Evaluatio

nof

supp

liers

environm

ental

perfo

rmance

Selectingof

green

supp

liers

Evaluatin

ggreen

supp

lier

developm

ent

programsfor

organizatio

ns

Indu

stry

An

illustrative

exam

ple

An

illustrative

exam

ple

An

illustrative

exam

ple

Anillustrative

exam

ple

Whitegood

smanufacturer

Turkey

LTF-LC

Dindu

stry

Taiwan

Electro

nic

company

Taiwan

Anillustrative

exam

ple

Telecom-

mun

ica-

tions

equipm

ent

provider

China

Automotive

indu

stry

Turkey

Evaluatio

nmetho

ds

Com

paris

onof

some

techniqu

essuch

asAHP

scoring

metho

dsand

DCF

techniqu

es

Know

ledge-

based

syste

m

Know

ledge-based

syste

ms(KB

S)and

case-based

reason

ing(C

BR)

multi-attribute

analysis(M

AA)

ahybrid

fuzzy

analytic

network

processa

ndfuzzy

PROMET

HEE

Delp

himetho

dand

thefuzzy

extend

edAHP

Data

envelopm

ent

analysis

(DEA

)and

ANP

Roug

hsettheory



Criteria Definition

EC1



























atrix

EC1

EC2

EC3

EC4

ECO1

ECO2

ECO3

ECO4

EMS1

EMS2

GP1

GP2

GP3

PC1

PC2

PC3

PC4

EC1

001387

001387

001387

001387

001994

012282

012500

005714

001556

00546

0002138

000000

001866

01046

00119

69000822

000000

EC2

010117

010117

010117

010117

006904

001104

002500

002857

002496

002830

006

413

007150

006001

000000

003512

004946

007753

EC3

005676

005676

005676

005676

003701

002535

002500

005714

009837

006

018

006

413

021451

006

001

003168

002275

008671

007753

EC4

002205

002205

002205

002205

007401

004

078

002500

005714

006111

005693

002138

007150

003233

005756

001628

004946

003877

ECO1

000796

004

658

004321

003594

005576

006154

002942

003630

007797

009063

001658

000000

003487

001084

000823

004

254

003527

ECO2

003893

000583

000825

001328

009425

006153

010975

0114

21003047

002483

001190

000

000

001162

003463

003662

000826

000720

ECO3

001430

000

604

000825

000

446

001112

001539

002912

001084

001359

002013

002036

000

000

001162

001295

002240

000522

001208

ECO4

001430

001702

001578

002180

003887

006154

003171

003865

007797

006

441

002091

000000

001162

001706

000823

001944

002092

EMS1

003774

005661

006

469

005032

010000

013333

00500

0013333

006

667

006

667

014461

000

000

007231

003774

002516

005661

005661

EMS2

003774

001887

001078

002516

01000

0006

667

01500

0006

667

013333

013333

000

000

000

000

007231

003774

005032

001887

001887

GP1

016380

016380

017677

010920

006

667

01000

0013333

01000

001000

0000

000

020123

042071

014184

016380

010920

016380

024571

GP2

000

000

000

000

009729

000

000

000

000

000

000

000

000

000

000

000

000

000

000

002930

006125

002364

000

000

000

000

000

000

000

000

GP3

016380

016380

005354

021840

013333

010000

006

667

010000

010000

020000

007679

016053

014184

016380

021840

016380

008190

PC1

015120

000

000

003474

008869

004541

008571

006756

010316

004

488

010924

003273

000

000

002723

014480

014480

014480

014480

PC2

015120

002907

00260

6003948

00244

7008571

009580

003788

001315

004

646

008036

000

000

013327

001958

001958

001958

001958

PC3

002520

018315

017923

013699

008472

001429

001421

003788

010939

001675

005693

000

000

007341

006516

006516

006516

006516

PC4

000000

011538

008757

006245

004541

001429

002243

002108

003258

002755

013729

000000

007341

009806

009806

009806

009806














ANP

TOPSIS
















Greenproducts

Pollutioncontrol


system





4 Application









Table4Limitsuperm

atrix

EC1

EC2

EC3

EC4

ECO1

ECO2

ECO3

ECO4

EMS1

EMS2

GP1

GP2

GP3

PC1

PC2

PC3

PC4

EC1

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

EC2

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

EC3

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

EC4

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

ECO1

00364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

5EC

O2

00246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

8EC

O3

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

ECO4

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

EMS1

00744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

1EM

S2004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

GP1

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

GP2

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

GP3

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

PC1

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

PC2

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

PC3

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

PC4

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988










119903119894119895=119891119894119895

radicsum119899

119895=11198912119894119895

(1)



119894119895is



V119894119895= 119908119894119895119903119894119895 (2)


119894 V

+

119899 = (Max V

119894119895| 119895 isin 119869) (Min V

119894119895| 119895 isin 119869

1015840)

(3)

119881minus= Vminus

119894 V

minus

119899 = (Min V

119894119895| 119895 isin 119869) (Max V

119894119895| 119895 isin 119869

1015840)

(4)





follows

119878+

119894= radic

119899

sum119895=1

(V119894119895minus V+119895)2

119894 = 1 119898 (5)

119878minus

119894= radic

119899

sum119895=1

(V119894119895minus Vminus119895)2

119894 = 1 119898 (6)









119862119894=119878minus119894

119878+119894+ 119878minus119894

(7)






5 Conclusions













119894119878+

119894119862119894








References
















































RoboticsJournal of





Journal of



RotatingMachinery





VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation











Criteria Definition

EC1



























atrix

EC1

EC2

EC3

EC4

ECO1

ECO2

ECO3

ECO4

EMS1

EMS2

GP1

GP2

GP3

PC1

PC2

PC3

PC4

EC1

001387

001387

001387

001387

001994

012282

012500

005714

001556

00546

0002138

000000

001866

01046

00119

69000822

000000

EC2

010117

010117

010117

010117

006904

001104

002500

002857

002496

002830

006

413

007150

006001

000000

003512

004946

007753

EC3

005676

005676

005676

005676

003701

002535

002500

005714

009837

006

018

006

413

021451

006

001

003168

002275

008671

007753

EC4

002205

002205

002205

002205

007401

004

078

002500

005714

006111

005693

002138

007150

003233

005756

001628

004946

003877

ECO1

000796

004

658

004321

003594

005576

006154

002942

003630

007797

009063

001658

000000

003487

001084

000823

004

254

003527

ECO2

003893

000583

000825

001328

009425

006153

010975

0114

21003047

002483

001190

000

000

001162

003463

003662

000826

000720

ECO3

001430

000

604

000825

000

446

001112

001539

002912

001084

001359

002013

002036

000

000

001162

001295

002240

000522

001208

ECO4

001430

001702

001578

002180

003887

006154

003171

003865

007797

006

441

002091

000000

001162

001706

000823

001944

002092

EMS1

003774

005661

006

469

005032

010000

013333

00500

0013333

006

667

006

667

014461

000

000

007231

003774

002516

005661

005661

EMS2

003774

001887

001078

002516

01000

0006

667

01500

0006

667

013333

013333

000

000

000

000

007231

003774

005032

001887

001887

GP1

016380

016380

017677

010920

006

667

01000

0013333

01000

001000

0000

000

020123

042071

014184

016380

010920

016380

024571

GP2

000

000

000

000

009729

000

000

000

000

000

000

000

000

000

000

000

000

000

000

002930

006125

002364

000

000

000

000

000

000

000

000

GP3

016380

016380

005354

021840

013333

010000

006

667

010000

010000

020000

007679

016053

014184

016380

021840

016380

008190

PC1

015120

000

000

003474

008869

004541

008571

006756

010316

004

488

010924

003273

000

000

002723

014480

014480

014480

014480

PC2

015120

002907

00260

6003948

00244

7008571

009580

003788

001315

004

646

008036

000

000

013327

001958

001958

001958

001958

PC3

002520

018315

017923

013699

008472

001429

001421

003788

010939

001675

005693

000

000

007341

006516

006516

006516

006516

PC4

000000

011538

008757

006245

004541

001429

002243

002108

003258

002755

013729

000000

007341

009806

009806

009806

009806














ANP

TOPSIS
















Greenproducts

Pollutioncontrol


system





4 Application









Table4Limitsuperm

atrix

EC1

EC2

EC3

EC4

ECO1

ECO2

ECO3

ECO4

EMS1

EMS2

GP1

GP2

GP3

PC1

PC2

PC3

PC4

EC1

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

EC2

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

EC3

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

EC4

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

ECO1

00364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

5EC

O2

00246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

8EC

O3

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

ECO4

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

EMS1

00744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

1EM

S2004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

GP1

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

GP2

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

GP3

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

PC1

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

PC2

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

PC3

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

PC4

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988










119903119894119895=119891119894119895

radicsum119899

119895=11198912119894119895

(1)



119894119895is



V119894119895= 119908119894119895119903119894119895 (2)


119894 V

+

119899 = (Max V

119894119895| 119895 isin 119869) (Min V

119894119895| 119895 isin 119869

1015840)

(3)

119881minus= Vminus

119894 V

minus

119899 = (Min V

119894119895| 119895 isin 119869) (Max V

119894119895| 119895 isin 119869

1015840)

(4)





follows

119878+

119894= radic

119899

sum119895=1

(V119894119895minus V+119895)2

119894 = 1 119898 (5)

119878minus

119894= radic

119899

sum119895=1

(V119894119895minus Vminus119895)2

119894 = 1 119898 (6)









119862119894=119878minus119894

119878+119894+ 119878minus119894

(7)






5 Conclusions













119894119878+

119894119862119894








References
















































RoboticsJournal of





Journal of



RotatingMachinery





VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation











atrix

EC1

EC2

EC3

EC4

ECO1

ECO2

ECO3

ECO4

EMS1

EMS2

GP1

GP2

GP3

PC1

PC2

PC3

PC4

EC1

001387

001387

001387

001387

001994

012282

012500

005714

001556

00546

0002138

000000

001866

01046

00119

69000822

000000

EC2

010117

010117

010117

010117

006904

001104

002500

002857

002496

002830

006

413

007150

006001

000000

003512

004946

007753

EC3

005676

005676

005676

005676

003701

002535

002500

005714

009837

006

018

006

413

021451

006

001

003168

002275

008671

007753

EC4

002205

002205

002205

002205

007401

004

078

002500

005714

006111

005693

002138

007150

003233

005756

001628

004946

003877

ECO1

000796

004

658

004321

003594

005576

006154

002942

003630

007797

009063

001658

000000

003487

001084

000823

004

254

003527

ECO2

003893

000583

000825

001328

009425

006153

010975

0114

21003047

002483

001190

000

000

001162

003463

003662

000826

000720

ECO3

001430

000

604

000825

000

446

001112

001539

002912

001084

001359

002013

002036

000

000

001162

001295

002240

000522

001208

ECO4

001430

001702

001578

002180

003887

006154

003171

003865

007797

006

441

002091

000000

001162

001706

000823

001944

002092

EMS1

003774

005661

006

469

005032

010000

013333

00500

0013333

006

667

006

667

014461

000

000

007231

003774

002516

005661

005661

EMS2

003774

001887

001078

002516

01000

0006

667

01500

0006

667

013333

013333

000

000

000

000

007231

003774

005032

001887

001887

GP1

016380

016380

017677

010920

006

667

01000

0013333

01000

001000

0000

000

020123

042071

014184

016380

010920

016380

024571

GP2

000

000

000

000

009729

000

000

000

000

000

000

000

000

000

000

000

000

000

000

002930

006125

002364

000

000

000

000

000

000

000

000

GP3

016380

016380

005354

021840

013333

010000

006

667

010000

010000

020000

007679

016053

014184

016380

021840

016380

008190

PC1

015120

000

000

003474

008869

004541

008571

006756

010316

004

488

010924

003273

000

000

002723

014480

014480

014480

014480

PC2

015120

002907

00260

6003948

00244

7008571

009580

003788

001315

004

646

008036

000

000

013327

001958

001958

001958

001958

PC3

002520

018315

017923

013699

008472

001429

001421

003788

010939

001675

005693

000

000

007341

006516

006516

006516

006516

PC4

000000

011538

008757

006245

004541

001429

002243

002108

003258

002755

013729

000000

007341

009806

009806

009806

009806














ANP

TOPSIS
















Greenproducts

Pollutioncontrol


system





4 Application









Table4Limitsuperm

atrix

EC1

EC2

EC3

EC4

ECO1

ECO2

ECO3

ECO4

EMS1

EMS2

GP1

GP2

GP3

PC1

PC2

PC3

PC4

EC1

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

EC2

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

EC3

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

EC4

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

ECO1

00364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

5EC

O2

00246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

8EC

O3

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

ECO4

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

EMS1

00744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

1EM

S2004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

GP1

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

GP2

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

GP3

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

PC1

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

PC2

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

PC3

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

PC4

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988










119903119894119895=119891119894119895

radicsum119899

119895=11198912119894119895

(1)



119894119895is



V119894119895= 119908119894119895119903119894119895 (2)


119894 V

+

119899 = (Max V

119894119895| 119895 isin 119869) (Min V

119894119895| 119895 isin 119869

1015840)

(3)

119881minus= Vminus

119894 V

minus

119899 = (Min V

119894119895| 119895 isin 119869) (Max V

119894119895| 119895 isin 119869

1015840)

(4)





follows

119878+

119894= radic

119899

sum119895=1

(V119894119895minus V+119895)2

119894 = 1 119898 (5)

119878minus

119894= radic

119899

sum119895=1

(V119894119895minus Vminus119895)2

119894 = 1 119898 (6)









119862119894=119878minus119894

119878+119894+ 119878minus119894

(7)






5 Conclusions













119894119878+

119894119862119894








References
















































RoboticsJournal of





Journal of



RotatingMachinery





VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation






















ANP

TOPSIS
















Greenproducts

Pollutioncontrol


system





4 Application









Table4Limitsuperm

atrix

EC1

EC2

EC3

EC4

ECO1

ECO2

ECO3

ECO4

EMS1

EMS2

GP1

GP2

GP3

PC1

PC2

PC3

PC4

EC1

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

EC2

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

EC3

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

EC4

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

ECO1

00364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

5EC

O2

00246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

8EC

O3

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

ECO4

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

EMS1

00744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

1EM

S2004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

GP1

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

GP2

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

GP3

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

PC1

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

PC2

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

PC3

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

PC4

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988










119903119894119895=119891119894119895

radicsum119899

119895=11198912119894119895

(1)



119894119895is



V119894119895= 119908119894119895119903119894119895 (2)


119894 V

+

119899 = (Max V

119894119895| 119895 isin 119869) (Min V

119894119895| 119895 isin 119869

1015840)

(3)

119881minus= Vminus

119894 V

minus

119899 = (Min V

119894119895| 119895 isin 119869) (Max V

119894119895| 119895 isin 119869

1015840)

(4)





follows

119878+

119894= radic

119899

sum119895=1

(V119894119895minus V+119895)2

119894 = 1 119898 (5)

119878minus

119894= radic

119899

sum119895=1

(V119894119895minus Vminus119895)2

119894 = 1 119898 (6)









119862119894=119878minus119894

119878+119894+ 119878minus119894

(7)






5 Conclusions













119894119878+

119894119862119894








References
















































RoboticsJournal of





Journal of



RotatingMachinery





VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation











Greenproducts

Pollutioncontrol


system





4 Application









Table4Limitsuperm

atrix

EC1

EC2

EC3

EC4

ECO1

ECO2

ECO3

ECO4

EMS1

EMS2

GP1

GP2

GP3

PC1

PC2

PC3

PC4

EC1

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

EC2

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

EC3

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

EC4

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

ECO1

00364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

5EC

O2

00246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

8EC

O3

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

ECO4

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

EMS1

00744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

1EM

S2004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

GP1

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

GP2

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

GP3

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

PC1

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

PC2

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

PC3

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

PC4

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988










119903119894119895=119891119894119895

radicsum119899

119895=11198912119894119895

(1)



119894119895is



V119894119895= 119908119894119895119903119894119895 (2)


119894 V

+

119899 = (Max V

119894119895| 119895 isin 119869) (Min V

119894119895| 119895 isin 119869

1015840)

(3)

119881minus= Vminus

119894 V

minus

119899 = (Min V

119894119895| 119895 isin 119869) (Max V

119894119895| 119895 isin 119869

1015840)

(4)





follows

119878+

119894= radic

119899

sum119895=1

(V119894119895minus V+119895)2

119894 = 1 119898 (5)

119878minus

119894= radic

119899

sum119895=1

(V119894119895minus Vminus119895)2

119894 = 1 119898 (6)









119862119894=119878minus119894

119878+119894+ 119878minus119894

(7)






5 Conclusions













119894119878+

119894119862119894








References
















































RoboticsJournal of





Journal of



RotatingMachinery





VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation










Table4Limitsuperm

atrix

EC1

EC2

EC3

EC4

ECO1

ECO2

ECO3

ECO4

EMS1

EMS2

GP1

GP2

GP3

PC1

PC2

PC3

PC4

EC1

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

003410

EC2

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

005703

EC3

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

006220

EC4

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

003777

ECO1

00364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

500364

5EC

O2

00246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

800246

8EC

O3

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

001313

ECO4

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

002613

EMS1

00744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

100744

1EM

S2004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

004723

GP1

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

015308

GP2

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

001451

GP3

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

013050

PC1

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

007690

PC2

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

005370

PC3

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

007829

PC4

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988

007988










119903119894119895=119891119894119895

radicsum119899

119895=11198912119894119895

(1)



119894119895is



V119894119895= 119908119894119895119903119894119895 (2)


119894 V

+

119899 = (Max V

119894119895| 119895 isin 119869) (Min V

119894119895| 119895 isin 119869

1015840)

(3)

119881minus= Vminus

119894 V

minus

119899 = (Min V

119894119895| 119895 isin 119869) (Max V

119894119895| 119895 isin 119869

1015840)

(4)





follows

119878+

119894= radic

119899

sum119895=1

(V119894119895minus V+119895)2

119894 = 1 119898 (5)

119878minus

119894= radic

119899

sum119895=1

(V119894119895minus Vminus119895)2

119894 = 1 119898 (6)









119862119894=119878minus119894

119878+119894+ 119878minus119894

(7)






5 Conclusions













119894119878+

119894119862119894








References
















































RoboticsJournal of





Journal of



RotatingMachinery





VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation


















119903119894119895=119891119894119895

radicsum119899

119895=11198912119894119895

(1)



119894119895is



V119894119895= 119908119894119895119903119894119895 (2)


119894 V

+

119899 = (Max V

119894119895| 119895 isin 119869) (Min V

119894119895| 119895 isin 119869

1015840)

(3)

119881minus= Vminus

119894 V

minus

119899 = (Min V

119894119895| 119895 isin 119869) (Max V

119894119895| 119895 isin 119869

1015840)

(4)





follows

119878+

119894= radic

119899

sum119895=1

(V119894119895minus V+119895)2

119894 = 1 119898 (5)

119878minus

119894= radic

119899

sum119895=1

(V119894119895minus Vminus119895)2

119894 = 1 119898 (6)









119862119894=119878minus119894

119878+119894+ 119878minus119894

(7)






5 Conclusions













119894119878+

119894119862119894








References
















































RoboticsJournal of





Journal of



RotatingMachinery





VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation

















119862119894=119878minus119894

119878+119894+ 119878minus119894

(7)






5 Conclusions













119894119878+

119894119862119894








References
















































RoboticsJournal of





Journal of



RotatingMachinery





VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation
















119894119878+

119894119862119894








References
















































RoboticsJournal of





Journal of



RotatingMachinery





VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation





















































RoboticsJournal of





Journal of



RotatingMachinery





VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation



















RoboticsJournal of





Journal of



RotatingMachinery





VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation











RoboticsJournal of





Journal of



RotatingMachinery





VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation









Documents

Research Article Evaluating Green Performance of Suppliers via Analytic … · 2019. 7. 31. · system [ ], analytic hierarchy process (AHP) [ ], fuzzy AHP [, ], a hybrid fuzzy analytic