Reverse logistics in effective recovery of products from waste materials

Patrick BeullensDepartment of Mathematics, University of Portsmouth, Portsmouth PO1 3HE, UK.(e-mail: patrick.beullens@port.ac.uk)

Key words: reverse logistics, economics of recovery, management of remanufacturing, management ofrecycling, collection system design

Abstract

Technical solutions for the recovery of products from waste materials become more and more available. Tohave these new technologies implemented in a real world, a feasibility study is indispensable. For thispurpose, it is often imperative to adopt the viewpoint of an individual firm and ask whether it would be wiseto engage in product recovery activities or not. Aspects of economics and logistics are of prime importancehere. Some important frameworks, models, and insights that have been developed in recent years aredescribed in this paper.

1. Introduction

Product recovery is an environmentally consciousapproach where products are returned from usersto be reused. Product recovery aims at recoveringthe residual value of used products. Recoveryoptions include the extension of the life span of aproduct or some of its parts (through repair andremanufacturing) or of materials (through recy-cling). Recovery prevents waste by divertingmaterials from landfills and conserves naturalresources (energy and materials).

Firms are often encouraged to offer productrecovery activities as a demonstration of corporatecitizenship. However, this may prove to be anunrealistic expectation since a rational firm willonly engage in profitable ventures; those thatincrease shareholder wealth (Guide & Van Was-senhove 2001). Whenever product recovery isfeasible from a technical point of view, it might notbe reasonable for an individual firm to engage inthese activities.

Based on our own research activities in thisfield, the main obstacles that have been identifiedwhen introducing product recovery in the eco-nomic landscape are highlighted. Importantframeworks, models, and insights that have beendeveloped in recent years are described. This

overview contributes to the conduct of feasibilitystudies of several (technical) recovery scenarios inwhich aspects of economics and logistics are ofimportance.

The discussion is structured in four main parts:(1) the acceptance of product recovery as a viableeconomic activity for an individual firm; (2)product recovery management for a remanufac-turing or recycling facility; (3) reverse logisticsnetwork design; and (4) aspects related to theeffective and efficient collection from (end-) cus-tomers.

2. Acceptance of product recovery

Technical solutions that transfer a returnedproduct into a product that could find some newuse become more and more available. Examplesare abundant: refilling toner cartridges, remanu-facturing single-use cameras, tire retreading,refurbishing electrical motors, remanufacturingIT-equipment, plastics recycling, compostinggreen household waste, etc. The fact that land-filling is prevented and that the (environmental)processing cost for the transfer is lower than the(environmental) cost to produce from virginmaterials, is not enough to have it implemented inthe real world. The question is whether it is

Reviews in Environmental Science & Bio/Technology (2004) 3: 283–306 � Springer 2005DOI: 10.1007/s11157-004-2332-3

worthwhile for a firm to engage in productrecovery activities.

2.1. Shareholder wealth

First, the firm will establish if these activities willincrease shareholder wealth. As pointed out byGuide and Van Wassenhove (2001), it may not bereasonable for every original equipment manu-facturer (OEM) to engage in product recoveryactivities. Fast growing firms, in for exampleelectronics and telecommunication, may need allthe available capital to invest in core activities. Thestock market is expecting high returns, and firmsmay require high return on capital expenditures orfavourable economic value analysis. It may berational for an OEM to not engage in reuseactivities, to subcontract, or encourage the start-up of corporate spin-offs. The decision whether ornot to engage in reuse activities directly, indirectly,or not at all is driven by a thorough economicanalysis of the costs and benefits of such a pro-gram for the individual firm. In the event thatproduct recovery is mandated, a careful economicanalysis is required to determine the best way to dothe recovery, including the best form(s) of recovery(remanufacturing, recycling, …).

2.1.1. Economic value addedGuide and Van Wassenhove (2001) propose themethod of Economic Value Added (EVA) as theprincipal framework to determine the potentialprofitability of reuse opportunities. EVA measuresthe difference between the return on a company’scapital and the cost of that capital. A positiveEVA indicates that value will be created for thefirm’s shareholders that satisfies their expectation;a negative EVA shows that value will not be cre-ated. The decision may be unprofitable for a largefirm in a market where high returns are requiredby stockholders, but profitable for smaller firmswhere lower returns may be acceptable. This mayin part explain the observation of Majumder andGroenevelt (2001) that smaller local firms oftenremanufacture a product even when the largerfirms (OEMs) have not started remanufacturing.

2.1.2. From waste stream to market-drivenmanagement

Guide and Van Wassenhove (2001) also advocatethe concept of Product Acquisition Management(PAM) as a key input to assessing the potential

economic attractiveness of reuse activities, and asa foundation for operational planning and controlactivities. PAM is part of a market-driven system,in which financial incentives should motivate end-users to return their products in the right quality toa firm specializing in the reuse of those products.The financial incentives could include depositsystems, credit toward a new unit, or cash paid fora specified level of quality. Firms are then able tocontrol the level of quality of returned productssince acceptance of returns is conditioned bystandards. The example given is that of a third-party remanufacturer of mobile telephones in theUnited States, which has adopted six nominalquality levels and six different associated pricesoffered for specific mobile phones that arereturned. A market driven approach will encour-age the formation of cascade reuse systems, whereproducts unprofitable for one firm to remanufac-ture may be offered to firms willing to recyclematerials.

The market-driven system is in contrast withwhat they call the waste stream system, wherefirms passively accept all product returns from thewaste stream, often including large volumes ofreturns of low recovery potential. They argue thatPAM in the market-driven approach has alsoseveral operational advantages in the recoveryfacilities compared to the waste stream approach,including lower inventory levels and work-in-pro-cess, better utilization of equipment, more stableand short lead times, and less leakage (disposal).Even if product returns may be mandated orencouraged by legislative acts, firms may stillencourage the returns of products in known con-dition by offering incentives. In such an environ-ment, a combination of the market-driven andwaste stream approaches is still possible.

The PAM/EVA approach is conceptuallyattractive, but a difficulty in the application is theestablishment of the exact relationship betweenthe offered set of incentives and the distribution ofthe returning products among the different qualitylevels. Also, the market’s willingness to purchaserecovered products has to be established. In anycase, it is recommended to use several estimates –pessimistic, neutral, and optimistic – in the anal-ysis. There are also other strategic considerationsto be made, which may complicate the assessmentof the value of product recovery. These issues arediscussed in the remainder of this section.

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2.2. Marketing and product design

Engaging in recovery activities may have implica-tions on several strategic levels. First, there aremarketing-related issues. A firm has to considerthe competitive advantages in adopting a greenimage. At present, very little research showing theeffects of a green image on sales is available.

2.2.1. Cannibalization effectA marketing-related strategic concern is the can-nibalization of new sales. There are risks in pro-viding recovered products that may compete forsales with the new products of the firm, and theserisks should be better understood. The situationwhere recovered products can find a market ofconsumers willing to pay the same or more thanfor a substitute new product, are rather theexception than the rule. Many recovered productshave a reputation problem, and as a consequence,have to be sold at lower prices to the low-endconsumers of a market. The relative price settingof new and recovered products will determine for aspecific market the relative volumes sold, and thequestion is which set of prices will maximizeshareholder value.

A framework for Price Setting Management(PSM) is found in the literature on market seg-mentation. Market segmentation literature studiesthe optimal pricing of independent products thatare differentiated by quality in a market of heter-ogeneous consumers whose valuations of qualityvary. However, in a product recovery setting, theremay be a strong dependence between the twoproducts: the supply of used products that can berecovered depends on the past sales volumes ofnew products. Furthermore, it also depends on thepercentage of products that are effectively col-lected and among those only a fraction will be fitfor recovery. Ferrer (2000) solves the market seg-mentation problem and finds that product recov-ery is not viable if the resulting cost savings are nothigh enough to price the recovered product aboveits marginal cost.

2.2.2. Product design impacts the levelof recoverability

The decision to engage in product recovery activ-ities may also be influenced by Product DesignManagement (PDM). Design features such asmaterial choice, design modularity, parts com-

monality across product generations, and dura-bility are critical planning decisions.

Product design may influence the recoverypotential. Consider, for example, the tire retread-ing business (see e.g. www.retread.org). A tire iscomposed of a tread, the outer layer of a tire indirect contact with the road, and a casing, theinner structure of the tire, which consists of rubberreinforced with steel cord. When the tire is worn,the tread can no longer be used, but the casing isoften still in good shape. Tire retreading is a pro-cess that replaces the worn out tread by a new one.By increasing the amount of steel cord in thecasing, a manufacturer of tires can increase thepercentage of collected tires that are retreadable.

Another example is whether or not to includemodern information technology into new elec-tronic products to increase the knowledge aboutproduct quality (Klausner et al. 1999). Sensor-based data recording devices and electronic dataloggers can be imbedded into, for example, newpower tools to record the peak load and temper-ature during usage. The chip, of course, has to bemounted on every new power tool in order torecord the data. Reading this data from a usedpower tool allows having a better assessment ofquality and as a result, increasing the fraction ofused products that can be remanufactured.

2.2.3. Price setting and product designIn the above two examples, tire retreading andpower tool remanufacturing, increasing the per-centage of recoverable products also increases theproduction cost of a new product. In addition, aremanfuactured power tool or retreaded tire isvalued less by consumers. In short, there are manysituations where it is reasonable to consider PSMand PDM simultaneously.

Is producing a remanufacturable productworthwhile? Debo et al. (2001) consider this issuein the context of simultaneous PSM and PDM,hence focusing on the simultaneous determinationof product prices and product design. In theirmicro-economic model, they consider a generalmarket structure for a monopolistic firm. Animportant characteristic in the model is the prod-uct parameter q (0 £ q £ 1), representing theremanufacturability level i.e. the fraction of usedproducts that can be remanufactured. The cost tomanufacture the new product, cn(q), is a convexfunction of q, while the cost to remanufacture a

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returned product, cr, is a constant. Assuming aused product has no value for the customer unlessit is remanufactured by the OEM, products areonly once remanufacturable, and all used productsbecome freely available for the OEM, it is foundthat it is profitable for the OEM to engage inremanufacturing and make its new product re-manufacturable if and only if:

mð0Þ ¼ ð1� dÞcnð0Þ � cr �dcnðqÞdq

����q¼0

> 0

where d (0 £ d £ 1) is the perceived depreciation ofa remanufactured product compared to the newproduct (the decrease in utility), and cn(0) is thecost of producing a single use, i.e. non-remanu-facturable, version of the product. They thus findthat the question whether to engage in remanu-facturing only depends on the production costsand the perceived depreciation. The consumertypes – whether there are many high-valuationcustomers or many low-valuation customers – areirrelevant, as long as all customer types exist. Itbecomes more likely that remanufacturing isprofitable if, all else equal, the production costs ofthe single use product are high, the perceiveddepreciation of a remanufactured product is low,the remanufacturing costs are low, or the requiredefforts to make a single use product remanufac-turable is low.

They also investigate the issue of how far to goin making the product remanufacturable (theproper value of q). It is found that this depends onthe market structure. A manufacturer chooses ahigher level of q in a market where relatively moreconsumers are interested in remanufactured prod-ucts and fewer are interested in a new product.Therefore, all else equal, the manufacturer has tosupply more remanufacturable products with fewernew products and therefore chooses a higher levelof q. In such a market, it is found that it may beoptimal that the new product may be sold at a loss(to capture their future value from selling themremanufactured). This is specific to productrecovery. Also specific to product recovery is that areduction in remanufacturing cost can lead toeither a decrease or an increase in the demand fornew products. If one would regard the new andremanufactured products as two substitutes ofdifferent quality without the supply restriction, thanthe new product will never be sold at a loss. Fur-

thermore, a reduction in remanufacturing cost willthen decrease the volume of new products sold.

Finally, Debo et al. (2001) find that the man-ufacturer may not find it profitable to collect allused products when a collection cost is incurred.In addition, the cost of recuperating the usedproducts may influence the remanufacturabilitylevel that the manufacturer builds into the prod-uct. With linear collection costs in the volumecollected, the model shows that the higher the unitcollection cost, the more low-end customers needto exist for the remanufacturability of the productsto be worthwhile.

2.2.4. Example: Tire retreadingTable 1 illustrates the use of the equationpresented in Section 2.2.3. Most of the data arebased on results from the retread industry(www.retread.org). Assume a new single-use trucktire costs $260 to produce, a retreadible new trucktire $286, and the cost of retreading $78/tire.Retreadable truck tires are being maintainedproperly by the transportation industry andreturned for retreading before the tread is com-pletely worn. Therefore, the remanufacturabilitylevel is high, about 80%. Similar values are givenin the table for car tires. In contrast with trucktires, however, car tires are used over a longerperiod of time, while being less intensively main-tained, and therefore, the remanufacturability levelis lower. It is estimated to be about 40%.

The value of remanufacturing is now calculatedfor various estimates of the perceived depreciation.There are reasonable indications that the truck tire

Table 1. Economic value of truck tire versus car tire retreading

cn(0)

($/tire)

q()) cn(q)

($/tire)

cn’(0)*

($/tire)

cr

($/tire)

d ()) v(0)

($/tire)

Truck tire

260 0.8 286 32.5 78 0.8 )58.20.6 )6.50.4 45.5

0.2 97.5

Car tire

100 0.4 110 25 30 0.8 )350.6 )150.4 5

0.2 25

* Derivative approximated by linear interpolation between 0and q.

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industry values retreaded tires much more than theusers of normal cars (most likely values for d are0.2 and 0.6, respectively). This results in a positiveevaluation of remanufacturing for the truck tirebut a negative evaluation for the car tire. Even ifthe remanufacturability level of car tires wouldincrease to 80%, the difference in perceiveddepreciation would keep these conclusionsunchanged. The bad reputation problem is oftenneglected in operations literature. However, it isprobably one of the main factors why the majorityof the truck tires are retreaded while passenger cartires are almost not being retreaded. Furthermore,the collection of passenger tires is more costly thanfrom the more structured market of distributiontransport. This places an even larger burden on theprofitability of retreading passenger car tires.

2.3. Aspects of competition in product recovery

The origin of competition in remanufacturing isoften the reverse logistics chain. The agents in thisreverse chain are responsible for gathering theused items, classifying and segregating them, andfinally transporting them to the manufacturer.They often take up some of the activities ofremanufacturing like disassembly and cleaning.The manufacturer cannot maintain completecontrol over the entire chain; this may give rise toopportunistic behaviour by some agents in thechain, particularly if the entire remanufacturingprocess can be duplicated.

Competition is a matter of considerable con-cern for OEMs. They have invested in the designand manufacturing of the item and may want tocorner the cost benefits of remanufacturing bytrying to put legal restrictions on local remanu-facturing or by product redesign that restricts theiraccess for local remanufacturers. On the otherhand, there are reasons from the viewpoint ofsociety to have local remanufacturing activities;the local remanufacturers may be quicker andmake the remanufacturing market more competi-tive. Communities and legislative bodies may beinterested in reducing waste disposal and maywant to increase net remanufacturing activity.

Majumder and Groenevelt (2001) give the fol-lowing example. Lexmark, a US-based printer andtoner cartridge manufacturer, took the followingactions when faced with fierce competition fromlocal remanufacturers:

� Lexmark introduced the ‘‘Prebate’’ programin April 1998. This program allows customersto get a $30 rebate off a $230 toner cartridge(Optra-S) if they agree to return the usedcartridge to Lexmark or destroy it (the car-tridge is also available without Prebate).

� Simultaneously, Lexmark sent letters to hun-dreds of smaller cartridge remanufacturersstating that they would face legal action if theyremanufactured Prebate cartridges.

� Some types of toner cartridges have anencrypted counter that must be reset by theOEM in order to continue printing.

Depending on the specifics of the situation, suchmethods can be considered to either restrict thelocal remanufacturer’s access to used items, or toincrease their cost of remanufacturing (or both).

Majumder and Groenevelt (2001) build agame-theoretic model to investigate the aspect ofcompetition between an OEM and a local reman-ufacturer. It is found that the OEM wants toincrease the local remanufacturer’s cost – whichmay even drive the local remanufacturer out ofbusiness. The local remanufacturer on the otherhand wants to lower the OEM’s production cost,in effect inducing the OEM to produce more newproducts. To stimulate remanufacturing, a socialplanner can give incentives to the OEM to increasethe fraction available for remanufacturing, orreduce his remanufacturing costs.

Although competition seems to shed a negativelight on product recovery, there are also somepositive points. First, it is found that it is possiblethat the OEM can make higher profits withremanufacturing in the face of competition thanwithout remanufacturing in a monopoly. Second, alocal remanufacturer may be interested in cooper-ating with the OEM to make used products avail-able to the OEM cheaply, in spite of being involvedin price competitionwith theOEMat the same time.

Finally, competitive models seem to be out-performed by models of full cooperation. In par-ticular, if the cost of local remanufacturers is nothigher than the remanufacturing cost of the OEM,the OEM may subcontract remanufacturing tolocal firms. Of course, there are many other factorsinvolved in such decisions as well. Obstacles thatmay need to be addressed are related to incentivealignment and information sharing. Factorsagainst subcontracting, for example, would be

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excessive coordination costs or the loss of vitalproprietary information.

2.4. Impact of legislation

The question whether product recovery is eco-nomically attractive or not has to be viewedwithin the legal framework in which the firmoperates. In the European Union (EU), a numberof recent legislative acts, known as producerresponsibility laws, require manufacturers to col-lect and reuse their products. In the EU producerresponsibility laws for electric and electronicproducts, 4 kg per inhabitant has been set as atarget for collection. Some sources claim that thereal volumes that arise are much higher. The EUmay increase the target in the future. Further-more, minimum levels of recycling have been seton collected products of certain product types.The requirements for firms doing business in theEU may act as entry barriers for firms not awareof the changes required for reverse logisticsactivities. Legislation in the United States tends toencourage, rather than mandate, reuse activities.However, more and more individual states havebanned the landfill of cathode ray tubes and someelectronics equipment, and the number of statesbanning specific products from landfill is expectedto grow.

Legislation may impose the (re)manufacturerto indicate that the product is a refurbished orremanufactured product, or that the productcontains recycled material or reclaimed parts. Aretreaded tire in the EU, for example, has to bemarked on the side to allow consumers to distin-guish it from a new tire. In general, this may havea positive or negative impact on the customer’svaluation of the recovered product. It is still aquestion whether labelling will ultimately lead tomore reuse and recycling.

Although global sourcing has become a keyfactor in many supply chains, the question iswhether this is equally beneficial for reverse chains.Furthermore, the movement of old products toother countries is an issue of great concern, leadingto many ‘‘not in my backyard’’ discussions. Arestriction on cross-border waste transportation,however, may limit the exploitation of large-scale,more efficient, waste recycling facilities.

Despite the new laws related to producerresponsibility and landfill bans, the current

amounts that are being reused or recycled are stillnot as high as desired by some social planners. TheEU is contemplating on legislative acts that specifya minimum recycling content in new products.However, lobbying by industry has resulted so farin fairly weak restrictions. It seems difficult toimpose such restrictions unilaterally withoutweakening the global competitive level of firms.Furthermore, it is currently not clear which formof recovery, including incineration with energyrecovery, is most appropriate.

One may also ask if by subsidizing remanu-facturing one could increase the number ofrecovered products and reduce the number ofnew products sold. When new products andrecovered products are considered substitutes,this may well have the desired effect. However, inthe case of product recovery it may also turn outto have the opposite effect, as indicated by themodel of Debo et al. (discussed in Section 2.2.3).A subsidy corresponds in their model to anexogenous decrease in remanufacturing costs. It isshown that this may increase the demand for newproducts. This effect is exactly the opposite ofwhat the legislator is expecting. Indeed, themanufacturer may be inclined to invest less inremanufacturability since this lowers its price fornew products and this could increase total salesand profits from new products.

Legislation is currently favouring the approachto let the manufacturers pay for disposal. This actslike an increase in the production cost of a newproduct, since all manufactured products willeventually be disposed of. The hoped for result isthe increase in the effective recovery level and a(relative) decrease in the total sales volume ofproducts containing only virgin materials. In moreand more states across the world, landfill costs andthe number of landfill bans of certain producttypes are expected to grow.

According to Ayres (1997), there is growingevidence that the use of extractive resources isunder priced whilst labour – which carries almostthe entire tax burden of government – is not. Heargues that governments may well start tore-allocate the tax burden towards the use of virginmaterials. This would certainly have an effect inthe economic evaluation of reuse and recyclingactivities in comparison with virgin material pro-duction.

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3. Obstacles within remanufacturing and recycling

Management of recovery operations differs sig-nificantly from conventional operations manage-ment. This statement is illustrated in the next twosections.

3.1. Product remanufacturing

In the literature, there seem to be a consensusabout the two main obstacles for product reman-ufacturing. First, there is the uncertainty involvedin the take-back process of returned products. Thisuncertainty comprises the variety, quality, quan-tity, and timing of the returning products. In orderto provide a buffer for fluctuations in productreturn and customer demand, remanufacturerstend to have very high stock levels. Unknownstates of the recovered parts leads to stochasticrouting and remanufacturing lead times, and ahigh degree of uncertainty in material planning.Another dominating obstacle is the necessity foran efficient and effective reverse logistics networkthat collects the interesting products from the(end-) customer to a processing facility.

The examination by Seitz et al. (2003) of aEuropean automotive engine remanufacturerillustrates these findings pretty well. It is observedthat there are more engines (cores) returned to theremanufacturer than are actually being used in theprocess. Core returns depend on engine break-downs and the engines returned are not necessarilythe ones required in the recovery process at thetime. There is, in other words, a difficulty in bal-ancing returns and demand, and one of the con-sequences are excessive inventories of cores.Exports of good used cars to other continents wereconsidered major obstacles. In the assembly pro-cess, small batch sizes are being used, and skilledpeople are needed throughout the process. Com-pared to conventional mass production, where alarge number of the same product is manufactured,remanufacturing is rather similar to the individualmaking of a few, handmade products. As a result ofthe small batch sizes, high changing times for toolsdetermine the process. Furthermore, workers needto be very skilled, not just to be able to deal withthe re-assembly, but also to be able to deal with thedifferent generations of engines in the disassembly,cleaning, testing, and sorting process.

Is the value recuperation of the cores able tooffset the costs added by the more difficult produc-tion environment and the more difficult reverselogistics process? It seems from their description,that this particular remanufacturer operates underthewaste streamapproach. Implementing amarket-driven approach implies designing a PAM program(see Section 2.1.2) in order to assess different levelsof quality at the beginning of the reverse logisticschain. The reverse logistics channel should then aimat providing only the interesting (good quality)cores to the remanufacturing facility, and cores oflesser quality should enter the proper (recycling)channels more early in the logistics network. Thiswould most likely reduce the uncertainty and thecosts in the reverse logistics network as well as in theremanufacturing facility. The reverse logisticschannel should be strengthened to avoid the leakageof good cars out of the system.One of the difficultieshere, clearly, is how to design the PAM program,given that the recovery potential of a product maybe difficult to assess before the actual product dis-assembly takes place.

3.2. Product recycling

Recycling firms are basically confronted with thesame obstacles as firms that remanufacture prod-ucts (see Section 3.1). The process, however, isorganized differently and is less impacted by theindividual quality of product returns.

Currently, only a limited percentage of electricand electronic products, henceforth called EEPs,can be realistically remanufactured or have partsreclaimed. The high labour-cost, the low marketvalue of the components, combined with productredesign and technology obsolescence precludemany remanufacturing efforts. Moreover, (weath-er) damage occurring at the use and collectionstages may limit parts reuse. For many EEPs,however, the revenue generated from recoveredmaterials, especially metals, may exceed the totalcost of take-back and recycling. Based on thetypical material composition of metal scrap, Rei-mer et al. (2000) report that one ton of electronicwaste, processed efficiently, can yield up to about$9000 if the metals are sold at market prices. AnEEP, however, may contain hazardous compo-nents for which the removal and treatment onlyadd costs, e.g. components containing berylliumoxide, batteries, capacitors, asbestos, some plas-

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tics, and LCD-Displays. Certain products maytherefore not be profitably collected and pro-cessed, and a fee must be charged to fund therecycling.

The product design and composition determineto a great extend the possible processing scenariosand the impurity levels achievable. In most situa-tions, disassembly is a first step in which hazard-ous or valuable targeted components are removed,and in a second step, the remaining parts areshredded into flakes and are sent to materialrecovery processors. These specialist processorsspecify maximum impurity levels and minimumvolumes for accepting product scrap (Das &Matthew 1999). The impurity level will alsodetermine the quality of the recycled material andthus the market price at which it can be sold.Aluminium for example is typically recovered intwo streams, high and low grade. High grade ismelted and then alloyed to industrial grade mate-rial. Low grade, containing impurities up to 10 to20%, is shredded, passes an eddy current separa-tor, and is then typically melted to remove oxides,gasses and other impurities. Because of the moreexpensive process, the price is typically less thanhalf of high grade. An optimal disassembly deci-sion will balance the cost incurred from disas-sembly with the profit that can be generated fromseparated parts and materials and the residualvalue present in the product. Prices on the marketcan vary considerably, e.g. prices for Palladium in1998 varied by a factor 20. For the typical mate-rials generated, there is no motivation to maintainlarge inventories since storage and holding costsquickly consume their value. When market pricesare low, it may therefore become more economicalto switch to less costly treatment processes thatgenerate materials with higher impurity, or even toabandon the processing of certain product types ifpossible.

The processing of different product types mayinteract. A mix of products may be processedtogether or separately, after separation. Metalscrap obtained from different processes may ormay not be blended, to achieve the requiredimpurity levels that are accepted by the subcon-tractor (Reimer et al. 2000). Steel, for example,because of its unique magnetic properties, is rela-tively easy to recover by shredding and thensending the flakes through a magnetic separator.Therefore, steel with a 30% impurity rate from

other metals, may be accepted. If the impurity islargely aluminium, then impurity may rise to 40%.Steel containing non-metal impurities, however,may only contain 10% impurity (Das & Matthew1999). The reclaimed steel is sent to a foundrywhere it is melted down and remaining impuritiesmay be released by heating it to high temperatures.Impurity level and batch size specifications maydiffer from one foundry to another, based on thespecific processes and technology they use. Deci-sions are related to the cost associated with thelevel of separation before the processing, and theprofit corresponding to (blended) material endstreams with various compositions.

Compared to the processing cost, the transpor-tation cost is often of the same order of magnitude,ormay even exceed it (Bettac et al. 1999). Especiallyfor large organizations having several local recy-cling centres, the proper selection of recycling cen-tres may be important. There is clearly a closeinteraction with the decisions to accept or buy end-of-life products, how and where to process, and towhom selling recovered parts and materials.

Summarizing, the profit for a recycler may begenerated from the combination of the acceptanceof various batches of EEP products, the feecharged to the generators, the selection of theprocessing location and scenario, and the selling ofthe recovered material scrap and components to asuitable specialist material processor or compo-nent re-user. These decisions have to be taken andrevised on a regular, e.g. monthly, basis.

3.2.1. A recycling process modelIn the context of the European RELOOP project(Esprit, No. 25552), a model has been developedthat takes these criteria into account with theobjective to maximize the recycler’s total revenue.For a detailed mathematical description, see Beul-lens (2001). Themodel is a generalized network flowmodelwith additional constraints, seeFigure 1 for agraphical representation of an example. There areorigin, destination, and transhipment nodes, andsome of the latter correspond to resources thatperform a transformation on the arcs flowing intothe node. Each origin node corresponds to a par-ticular batch of products supplied at a particularlocation or to inventories of (un)processed productsavailable from the previous planning period. Eachdestination is associated with a set of end streams,possibly a blend of components, delivered to a

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particular subcontractor, or with end inventories tobe transferred to the following planning period.

The model is fairly general. Both push and pulldriven supply can be incorporated. Push drivensupply can represent agreed or mandatory pro-cessing. However, capacity or demand shortagesmay cause that not all supply is accepted. Pulldriven supply can be applied to identify items thatcan be profitably processed and marketed usingavailable remaining capacity. Likewise, push andpull driven demand can be modelled. A pulldemand can represent a target value, set e.g. in along-term contract with a specific specialist pro-cessor. Excess demand is incorporated to allow forthe processing of push driven collection whencapacity is available. Finally, the generality in thismodel is mainly related to its flexibility to modelthe specific process options available at the recy-cler, as illustrated by the following example.

3.2.2. ExampleA simplified example shows how the recyclingmodel works. Basically, a recycling process deci-sion tree is constructed that includes all the

possible processing options available to the recy-cler. The example further illustrates the effects of amandatory (push) versus a voluntary (pull) col-lection program.

A recycling company operates two workingcentres (Figure 1): a manual disassembly centre,and a shredder facility specialized in electronicscrap (E.S.S.). Two electronic product types, Aand B, are being offered, each at two differentlocations.

Product A can be manually disassembled usingpneumatic tools into the following fractions:microprocessor, iron screws and covers, aluminiumcase, Printed Board Assembly (PBA), copper cable,and mixed plastics. Any disassembly operation inFigure 1 is indicated by a bow covering the arcs thatrepresent the outflows of the disassembly process.As an alternative, in the E.S.S. shredder facility, theproduct is first shredded and a magnetic separatorrecovers the ferrous parts. The non-ferrous fractionis transferred to a riddle, separating the smallerparts (< 15 mm) (fluff). The remaining largerfraction is fed to an eddy-current separator wheremetals such as aluminium are recovered. The

Al high

Market

Cu (cable)

Microprocessor

Al case

Cu (cable)

Iron

PBA

Plastics mix

Al mix

Specialist processorMaterialProcessOrigin

Metal mix

Cu mix

Al mix

Cu mix blend

Cu mix

Waste to energy

Filler material

Batteries recyclingBatteries

Plastics mix

Fluff

Fluff

Al mix

Cu mix

Metal mix

B

B

A

A

Manualdisassembly

E.S.S.

E.S.S.

Manualdisassembly

Steel

Figure 1. Recycling process decision tree for two products A and B, using manual disassembly and/or an electronic scrap shredderfacility E.S.S. A disassembly operation is indicated by a bow covering the arcs that represent the outflows of the process. A blendingoperation is indicated by a dotted bow covering the inflows.

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remaining fraction contains mainly copper, pre-cious metals and the parts of the PBA. For productB, a manual disassembly step first separates thebatteries and the plastics, and the remaining part issent to the E.S.S., resulting in: a metals mix, alu-minium low grade, a copper mix, and fluff.

The resulting material fractions all go to aspecific market or a specialist processor (Figure 1).Additional data for the example is given inTable 2. It is assumed that there is a constraint setby the copper mix processor in that the totalamount of impurities, X, must be smaller than40%. This causes a problem for product A to passthe E.S.S., since X is 50%, but in combination withthe copper mix of product B, having X ¼ 30%,specifications may be met. We therefore create twodemand nodes for the copper smelter; one for theunblended material, and another one for the casethe copper mix of A and B are blended. Theblending operation is indicated in Figure 1 by adotted bow covering the inflows of the blendingprocess.

The data is used as input for the recyclingprocess model. The model is solved with linearprogramming techniques. Table 3 summarizes the

differences between various push (mandatory) andpull (voluntary) scenarios for A and B, assuming asupply of 200 ton of A as well as B. The first twocolumns on the left in this table are additionalinputs of the model. The remaining three columnson the right are part of the model output. In theabsence of B, processing A is unprofitable, themanual disassembly is chosen, and the fee chargedto the customer offering these products should atleast be 0.06 /kg. Also processing B is notprofitable, with a total cost of 0.085 kg)1. Whenprocessing A and B are both mandatory, theE.S.S. processing option for A becomes feasible,and since it turns out that the E.S.S. gives a netprofit for A, the total cost for processing is only0.015 kg)1. The same occurs when A is mandatoryand B is voluntary; some amount of B will beselected to allow the processing of A in the E.S.S.If B is mandatory and A voluntary, the wholeavailable amount of A can be accepted and passthe E.S.S. to lower total costs. In the scenario of acapacity restriction on the E.S.S. and A pushedand B pulled, the proper mix of A and B will beprocessed in the E.S.S. to fill up its capacity and toassure that the copper mix fulfils the quality

Table 2. Data and parameter settings

Product Process Material Weight Cost*

(%) ( /kg)

A Manual Disassembly1 Microprocessor 2 )0.4Iron screws and cover 29 )0.06Aluminium case 38 )0.98Printed board assembly 12 )0.36Copper cable 8 )0.36Plastics mix 11 0.2

)0.02E.S.S.2 Ferrous metal mix 33 )0.06

Copper mix (X = 50%) 45 )0.16Aluminium mix 22 )0.38Fluff 1 0.02

B Manual Disass. + E.S.S. Ferrous metal mix 10.5 )0.06Copper mix (X = 30%) 27.3 )0.16Aluminium mix 2.94 )0.38Fluff 1.26 0.02

Plastics mix 38 0.2

)0.02Batteries 20 0.3

* Including transport cost, specialist processing cost and market value.1 0.5 /kg collection and processing cost.2 0.15 /kg collection and processing cost.

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constraint (X £ 40 %), while the remainingamount of A is manually disassembled. When B ispushed and A is pulled under the capacityrestriction, the remaining capacity is used toprocess A.

The example shows that process selection maybe influenced by various parameters: the offeredavailable product types, the process logic, thepossibilities to blend, the capacity restrictions andthe cost structure. In practice, the copper mix willresult in the extraction of other components aswell, e.g. gold, palladium, and silver. More avail-able specialist processors for copper mix, steel, andaluminium mix may be available, each having itsown prices and quality limitations. More producttypes are generally processed, and more processoptions may be available, possibly at differentlocations. The solution then becomes less ‘‘obvi-ous’’, and tools using models such as this one mayprovide valuable assistance to the selection of themost optimal solution.

4. Designing the product recovery network

The implementation of product recovery requiressetting up an appropriate logistics infrastructurefor the arising flows of used and recovered prod-ucts. Physical locations, facilities, and transporta-tion links have to be chosen to convey the productsfrom their former users to a producer and fromthere to future markets. In Sections 2 and 3, the

importance of the reverse logistics network tosupport product recovery activities has been dis-cussed in the light of the market-driven approach,competition, and leakage control. In this section,the issue of designing the product recovery net-work itself is addressed.

Based on an extensive survey of models in theliterature, Fleischmann et al. (2001) identify thefollowing three generic characteristics of productrecovery networks.

� The coordination requirement. Recovery net-works form a link between two markets,namely a ‘‘disposer market’’ where usedproducts are set free by their former users anda ‘‘reuse market’’ with demand for recoveredproducts. Both markets may coincide, result-ing in ‘‘closed loop’’ goods flows, or be dif-ferent, forming an ‘‘open loop’’. Typical stepsduring the transition from disposer to reusemarket include collection, inspection and sep-aration, re-processing, re-distribution, anddisposal. In general, the network includes aconvergent part on the collection side, adivergent part on the distribution side, and anintermediate part depending on the specificre-processing steps. This role of recoverynetworks as an intermediate between twomarkets gives rise to a coordination issueconcerning supply and demand.

� The supply uncertainty. The availability of usedproducts for recovery is much more difficult to

Table 3. Results of the model (last three columns) for various push (mandatory) and pull (voluntary) scenarios, assuming a supply of200 ton of product A (B) if available

Products available Push / Pull Processes selected Quantities processed

(1000 kg)

Total cost

( /kg)

Unrestricted capacity E.S.S.

A Pull / / /

A Push Manual 200 0.06

B Pull / / /

B Push E.S.S. 200 0.085

A + B Push E.S.S. 400 0.015

A + B Push A / Pull B E.S.S. 200 (A), 160 (B) 0.0068

A + B Pull A / Push B E.S.S. 400 0.015

Restricted capacity E.S.S. to

250.000 kg / planning period

A + B Push B E.S.S. 50 (A), 200 (B) 0.057

A + B Push A Manual 61 (A) 0.017

E.S.S. 139 (A), 111 (B)

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control than the supply of input resources in atraditional supply chain. Therefore, there maybe a considerable mismatch between supplyand demand with respect to timing and quan-tity in a recovery network. The availability andthe quality of used products are, in general, notknown beforehand, which makes supplyuncertainty a major characteristic of recoverynetworks.

� The inspection, separation and choice oftreatment. As a direct consequence of thesupply uncertainty, separation and inspectionbecome important issues in this context. Ingeneral, not all (components of) the collectedproducts can be reused in the same way.Rather, feasibility of recovery options maydepend on the condition of the individualproduct. For example, a used copy machinemay be refurbished and sold on a secondarymarket if it is in good condition. If it is wornout, certain components may still be reusedas replacement parts, whereas material recy-cling may be the only resort for heavilydamaged machines. Since the quality of areturned product is, in general, not knownbeforehand, an appropriate disposition – andhence the destination of the product flow –can only be determined after inspection andtesting. Moreover, even if technically feasible,a recovery option may not be economicallyattractive. Since total recovery costs dependon transportation and hence on the logisticsnetwork structure, designing the recoverynetwork sets important constraints for theeconomical viability of recovery options.

Two main questions are of importance. First, howdoes product recovery alter the network design ofa supply chain? In many cases, recovery networksare not set up independently ‘‘from scratch’’ butare intertwined with existing logistic structures.This is particularly true if products are recoveredby the OEM. In this case the question ariseswhether to integrate collection and recovery withthe original ‘‘forward’’ distribution network orrather to separate both channels. To this end, it isimportant to know how much product recovery isrestricted by the constraints that are implied by theexisting logistics infrastructure. This question isthe more important since many companies havegone through a major redesign phase of their

logistics networks recently, notably in Europe.Global logistics structures have replaced nationalapproaches. However, in many cases productrecovery has not yet been taken into account. Thisraises the question whether product recovery willrequire another fundamental change in logisticsstructures or whether it can efficiently be inte-grated with existing ones. Therefore, a firstimportant question is how product recovery altersthe network design of a supply chain.

Secondly, supply uncertainty has been identi-fied as a major characteristic of recovery networks.What is the impact of the uncertainty in supply ofreturned products on the network design? Toassess its impact on network design, it is helpful tofirst analyse the impact of (deterministic) supplyvariations.

Fleischmann et al. (2001) have investigatedthese issues. The remainder of this section willelaborate on their modelling approach and theirfindings. A generic product recovery networkdesign model, a so-called mixed-integer-linearprogramming model, was build that took theabove characteristics into account. They considerthree intermediate levels of facilities, namely dis-assembly centres where the inspection and sepa-ration function is carried out, factories for there-processing and possibly new production, anddistribution warehouses. Moreover, two disposi-tions for the collected goods are considered,namely recovery and disposal, where recovery isonly feasible for a certain fraction of the collectedgoods. The general structure of this network isdisplayed in Figure 2.

Analogous to traditional facility locationmodels, the objective is to minimize a total costfunction, and the decisions relate to the numberof facilities to open, their locations and the allo-cation of the corresponding product flows. Fur-thermore, there are technical and economicrestrictions imposed on the reusability and reuseof returning products, respectively. Productsshould be disposed of due to the technical or theeconomical infeasibility of a fraction of returningproducts. There is, in other words, an additionaldegree of freedom concerning the issue of dis-posal, since it is allowed to locally dispose oftechnically good products due to economic rea-sons. This could be the case when e.g. returnsfrom certain regions are too far from productionfacilities. It should be noted that the ‘‘disassembly

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centres’’ in the model refer to any form ofinspection and separation installations ratherthan being restricted to mechanical disassembly ina strict sense. What is essential is that feasibilityof recovery options for the individual products isdetermined at this stage. Similarly, ‘‘disposal’’may include any form of recovery that is out-sourced to a third party, e.g. material recycling. Itis only required that this flow leaves the networkat the disassembly centres.

The model formulation is fairly general and canreflect many different recovery situations. Firstly,different market structures can be taken intoaccount. First, a particular customer may be partof the reuse market, the disposer market, or both.Secondly, both push (collection obligation) andpull driven collection (market-driven approach)can be expressed, describing the economics of thedisposer and the reuse market, and this may wellbe dependent on the region of the customers sothat differences in regional economic or regulativefactors can be considered. Thirdly, a regular pro-duction source (availability of new virgin materi-als) in addition to product recovery can beincluded or suppressed.

The model was intensively tested for two cases:copier remanufacturing and paper recycling (Fle-ischmann et al. 2001). A detailed numerical anal-ysis on these cases was carried out to investigate:

� if adding a recovery network to an existingforward network (sequential design) entailssubstantially higher costs than the simulta-neous design of forward and reverse network(integral design),

� the impact of different return rates on thenetwork design.

4.1. Example 1: Copier remanufacturing

The copier remanufacturing example followed inbroad terms the direction of several case studies oncopier remanufacturing. Major manufacturerssuch as Xerox, Canon, and Oce are remanufac-turing and reselling used copy machines collectedfrom their customers. For it to be considered forremanufacturing, a used machine must meet cer-tain quality standards, which are checked duringan initial inspection at a collection site. Remanu-facturing is often carried out in the original man-ufacturing plants using the same equipment.Machines that cannot be reused as a whole maystill provide reusable spare parts. The remainder istypically sent to an external party for materialrecycling. In this example, the focus is on theremanufacturing and recycling/disposal options.The design of a logistics network for copierremanufacturing was placed in a European con-text. The copier manufacturer serves retailers in 50major European cities (capitals plus cities withmore than 500,000 inhabitants). Customerdemand at each retailer is assumed to be propor-tional to the number of inhabitants of the corre-sponding service region.

In a first step, a ‘‘traditional’’ situation withoutproduct recovery is considered. In this case, astandard ‘‘forward’’ production-distribution net-work is determined, i.e. the locations for plantsand distribution warehouses and the allocation ofthe resulting goods flows. The bold lines inFigure 3a show the resulting optimal forwardnetwork, consisting of one central manufacturingplant in Frankfurt and five regional warehouses inFrankfurt, London, Barcelona, Milan, and Bel-grade. For the sake of clarity, the flows to andfrom the customers have been omitted. Each cus-tomer is assigned to the closest warehouse. Totalcosts for this solution amount to k 44,314.

Assume now that product recovery is intro-duced as an additional activity, which has to beintegrated into the existing forward network.Suppose that the return volume of used productsamounts to 60% of the sales for each retailer.Moreover, due to environmental regulation andservice considerations all returned products haveto be collected. After inspection, 50% of the

Figure 2. General structure of the recovery network designmodel.

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returned products turn out to be remanufacturablewhile the remainder has to be sent to an externalmaterial recycler. To design the return network,locations for the inspection/disassembly centresand allocations of the return goods flows need tobe determined. Note that this includes a disposi-tioning decision for the remanufacturablemachines, which may but do not have to be reused.The dotted lines in Figure 3a show the optimalreturn network, comprising six regional inspectioncentres located in Frankfurt, London, Paris,Valencia, Milan, and Budapest. Moreover, it turnsout that all machines that are technically accept-able should actually be remanufactured. Totalcosts (including the forward network) are k45,366. The forward and the return network arevery similar in this example. This may not besurprising since the degree of freedom for thereturn network design is fairly limited due to thefixed forward structure.

To assess the impact of this restriction, anintegral design optimizing both forward andreturn network simultaneously is finally consid-ered. Figure 3b shows the optimal integrated net-work for this example. It turns out thatthe optimal network now decomposes into twoparts with manufacturing plants in Paris andBerlin, respectively. Clearly, the structure of thissolution differs significantly from the network inFigure 3a. The product return flow, therefore, canhave an impact even on the forward networkdesign. Due to the additional goods flows, productrecovery is a reason for decentralization in this

example. However, considering the cost effectsputs this picture in a different perspective: totalcosts for the integrated solution amount to k45,246, which comes down to savings of less than1% with respect to the sequential approach.Hence, for this example, the sequential and theintegrated recovery network design approach leadto different solutions but cost differences are neg-ligible. In other words, the fixed forward networkstructure does not impose significant restrictionson the design of an efficient return network.Clearly, this is good news for the manufacturerstarting to engage into product recovery. Essen-tially the same results were found in many otherscenarios for varying input parameters.

4.2. Example 2: Paper recycling

This case is motivated by European paper recy-cling business. Waste paper comprises about 35%of total household waste volume in Europe. At thesame time, increasing demand for pulpwood inpaper production puts a heavy burden on forestecosystems. Therefore, paper recycling has been amajor issue for at least 20 years now. In thiscontext, consider the design of a logistics networkfor a European paper producer. Customers andpotential facility locations are the same as inExample 1. However, it is necessary here to takeinto account an additional cost element, namelyraw material transportation. Assume that pulp-wood is exclusively supplied from forests inScandinavia and adds its transportation as a

Figure 3. Optimal sequential (a) and integrated (b) network for copier manufacturing.

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location dependent element to the productioncosts. Moreover, assume that transporting pulp-wood is significantly more expensive than trans-porting paper.

Again, a pure ‘‘forward’’ network without col-lection and recycling is analysed first. The boldlines in Figure 4a show the resulting optimalsolution consisting of a central production plant inStockholm and five regional warehouses in Stock-holm, Hamburg, Saragossa, Milan and Krakow.Total costs for this solution amount to k 19,570.

Second, recycling of waste paper is included.For this purpose, pre-processing centres need to beinstalled where collected paper is sorted andcompacted and then transported to a productionplant. Processing centres play the same role asdisassembly centres in Example 1. A maximum of70% of the sales volume is assumed to be availablefor collection at each customer. For comparison,note that EU directives set minimum targets ofrecycled paper content for packaging material of60%. In line with current policy, assume no take-back obligations for used paper. Hence, collectionfollows a pull approach. Finally, assume that 10%of the collection volume is extracted at the pre-processing centres as being non-recyclable. Thedotted lines in Figure 4a indicate the optimal col-lection network in this case. Six regional pre-pro-cessing centres are located in Stockholm, London,Paris, Milan, Hanover and Wroclaw. Moreover,collection in southern Europe turns out not to beeconomically attractive, including the Iberian

Peninsula, southern Italy, and the Balkan. Theadditional logistics cost are too high to transportthe used paper to the central recycling facility.Total costs of this network, including the fixedforward locations, amount to k 17,990.

Finally, for this example an integral designoptimizing forward and return network simulta-neously leads to results shown in Figure 4b. As inExample 1 the optimal network now decomposesinto two parts. A plant in Stockholm now onlyserves the northern and northeastern part of Eur-ope, while all other countries are served from anew plant in Brussels. Note that this result is inaccordance with what is observed in industry. Thecollection strategy has also changed when com-pared to the sequential approach. With exceptionof Athens and Palermo collection is now beneficialat all locations. As a consequence, the number ofpre-processing centres increased to eight. How-ever, what is even more significant is that the totalnetwork cost decreased to k 14,540, which isabout 20% lower than the sequential design.Hence in contrast with Example 1, optimizing theforward and the return network simultaneouslynot only leads to a different solution than asequential approach in this case, but also results ina significant cost benefit.

4.3. Network design: Conclusions

The following general conclusions are made. Dif-ferent results in both cases are found: while the

Figure 4. Optimal sequential (a) and integrated (b) network for paper recycling.

297

integral design, in general, results in a moredecentralized network, cost differences are signifi-cant only in the paper recycling example. In gen-eral, forward flows dominate the network design.The impact of return flows increases with adecreasing number and uniformity of potentialfacility locations and with an increasing economicincentive for product recovery, namely higherproduction cost savings, higher penalty costs forrejecting collection, and higher disposal costs. Onlya significant impact of return flows on the forwardnetwork is found, and hence a cost differencebetween the integral and sequential design, in caseof a major structural difference between forwardand reverse channel cost structures together withhigh return volumes, as in the paper recycling case.

This is good news in the sense that productrecovery can in many cases be implemented with-out requiring major changes in the existing ‘‘for-ward’’ production-distribution networks.Moreover, separate networks can be expected to bemuch easier to deal with organizationally. A com-pany can create a new, dedicated organizationalunit to deal with return flows. Therefore the cost ofcoordination and restructuring tends to be lower.

From a methodological point of view theobserved robustness means that forward andreturn networks can be modelled separately inmany cases, significantly reducing the problemsizes. Finally, these results suggest that supplyuncertainty can be expected to have a limited effecton the network design and that a deterministicmodelling approach appears to be appropriate forthe recovery network design in most cases. Long-term non-stationary effects as implied by startingup and extending product recovery activities maybe an argument for multi-period models, whichcertainly deserve further attention.

5. Design of the collection system

It is not yet known to what extent reverse logisticsmight increase the total amount of transportationin supply chains – partially since it will also reduceactivities related to the use of new, extractiveresources. It is clear, however, that the extratransportation will diminish the environmentalbenefits of closing the loop. Likewise, inefficient orineffective transport activities limit the economicsuccess of reprocessing products. In this final sec-tion, it is shortly discussed how the collection and

transport system may be designed, and what theimportant parameters for optimization are.

First and foremost, there is the question ofnovelty. How does the collection of old productsdiffer from the distribution of new products? Insome contexts, there aren’t any significant newissues. Return flows of low value which may beconsolidated to form large batches, can be col-lected by firms deploying container transportersand/or transport by rail, waterways, or sea. Otherthan the issue of perhaps transporting invaluablegoods, there is no significant difference with thetransport of bulk materials. Valuable items, suchas repairable airplane parts or refillable copiercartridges, can be transported by common carrier,parcel post, or express services. These transportcompanies do not make a distinction for theirplanning between ‘‘normal’’ goods and productsthat are part of a reverse logistics flow. Such caseshardly need any further discussion, yet it would beunjust to generalize. Beullens et al. (2004) providethe following examples to introduce some of thenew issues that can arise due to increased returnflows from customers.

� Collecting from industrial firms. A specialistrecycler in the U.K. collects products with ahazardous content from car repair centres,such as oil filters, fluorescent tubes, oil rags,and car batteries. The goods are collectedevery month or every three months. There arethree depots in the U.K., and the country isdivided into a set of 30 sectors. Every week,collection vehicles visit some of these sectors.One of the issues the considered company facesis designing the sectors so as to meet the desiredperiodic collection schedules at the lowest cost.There are two cost factors: the number ofvehicles needed per week and the variablerouting cost. The company wishes to minimizethe hiring of extra vehicles and tries to workwith a fixed set of company-owned vehicles.Therefore, balancing the workload by sectordesign is considered an important objective.

� Collecting from households and small busi-nesses. The cost of collection per unit of massvaries from city to city and region to region.Empirical findings about the efficiency ofrefuse collection schemes are reported in theliterature. While a part of these differences arethe result of differences in demographics and

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demand, another part can be attributed to thevariety in the organization. For example, thecosts differ, ceteris paribus, between a systemthat uses kerbside collection and one where thecollection occurs from drop-off sites, whetherhigh or low collection frequencies are in place,whether regular or irregular (continuallyre-optimized) collection schedules are beingused, etc. Some of these studies report theobserved changes in collection cost and quan-tities due to the introduction of a source sepa-ration program. Instead of collecting aheterogeneous stream of products at one time,the stream is now divided into distinct classesat the collection point. The primary purpose isto facilitate the separate reprocessing of eachclass in specific recycling units. One of theissues is the new collection frequency of eachstream and deciding when to visit each collec-tion point. Decisions should optimize theoperational efficiency within the boundaries ofthe social and political constraints. A relatedissue is whether to collect those separatestreams in a single combined visit with onetruck, or separately, with two stops made bydifferent vehicles. How do source separation,visit frequency, and collection method affectthe transport cost?

� Integrating deliveries and collections. Severaltake-back schemes are reported in the literature,including printer cartridge recycling in GreatBritain, power tools recycling in Germany,worldwide take-back and reuse of single-usecameras, and worldwide collection and refur-bishing of IT equipment. In these cases, trans-portation of old products is combined withdelivery of new products. While distributionschedules are usually fixed, there is more free-dom in specifying the moment the old productsare collected. Returns can be collected duringthe next delivery, but the collection may also bepostponed until a larger quantity is available. Insome retail chains, deliveries occur daily to everystore, and returns are only collected every twoorthree days. How to determine the optimalpostponement policy? In addition, vehicleroutingmayneed to take into account strict timewindows for delivery, especially regarding foodstores, with possibly a separate compartment inthe vehicle reserved for cold storage. Collectingreturning goods may get in the way.

A common observation in these cases is the pres-ence of two decision levels. On the highest level,the decisions concern the design of the system,such as the customer service policy. The challengeis to design the system so as to fully exploit thefeatures specific to reverse logistics, in particularthe available degrees of freedom. On the lowerlevel, vehicle routing problems are solved takinginto account the specific design and relevantadditional constraints.

5.1. General collection system designconsiderations

The design of the system should meet the generalrequirements of effectiveness and efficiency. Prod-uct recovery starts with the effective acquisitionfrom the generators (former users). The aim,clearly, should be to avoid the targeted productsending up in (unwanted) waste streams. The gen-erators must be willing to participate consistently.This behaviour can be stimulated by assuring thatthe collection program delivers good service. Theservice must be convenient and consistent in time.At best, it will offer the lowest cost alternative. Thesecond requirement for effectiveness is to designthe collection and transport system in view of thetargeted reprocessing application. Reuse naturallyrequires that products are returned in the bestpossible condition and are shielded from any sortof (weather) damage. Material recovery, however,can often bear less careful handling. The productsalso need to be transported in a cost-efficient wayto the facilities of the reverse logistics network.Efficiency may call for the temporary storage andaccumulation of products before being shipped,volume compaction, source separation, specialvehicle characteristics, etc.

5.2. Collection system design aspects

A distinction is made between four aspects: thecollection infrastructure, the collection policy, thecombination level of the collection, and the char-acteristics of the collection vehicles.

5.2.1. Collection infrastructureThe collection infrastructure relates to the points atwhich generators hand over the used products to thenetwork. The three prominent types are as follows.

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(1) On-site collection. Used products are collectedon the premises of the generator. This type ofcollection is often applied to commercial firmsor for the kerbside collection of refuse andrecyclables from households.

(2) Unmanned drop-off sites. The generators bringthe products to large storage containers at adesignated location in the neighbourhood.This is often used as an alternative to kerbsidecollection for refuse or separated recyclablessuch as glass bottles, paper, or textiles.

(3) Staffed and smart drop-off sites. Staff super-vision allows for a more selective acquisitionand careful separation. Municipal collectiondepots, second-hand shops, and even regularshops and retailers can all fulfil this function.Smart drop-locations are ‘‘intelligent’’unmanned drop-off sites with a similar pur-pose. They are relatively new and are currentlyused for recyclables or reusable packaging (tincans, bottles). A smart glass collectionmachine, for example, automatically sortsbottles according to colour and does notaccept other products. In addition, themachine shreds the bottles to maximize theuse of its capacity. Equipped with monitoringdevices and telematics, it signals informationon the remaining capacity or any malfunctionto the collector.

Introducing more systems in parallel usuallyincreases the capture rate; for example, installingdrop-off sites both at the retailers and at themunicipal refuse collection depots. The integrationwith existing programs, in particular with the localrefuse collection system, can be appropriate andhas the advantage of familiarity. The collectionmight also be organized infrequently and ad hoc.For example, generators can be invited throughthe local media to bring the products to themunicipal depot during a specific ‘‘collectionweek’’. Or, vehicles can make short stops nearconvenient locations such as schools and churches,providing in this sense ‘‘mobile’’ drop-off sites.

5.2.2. Collection policyThe collection policy specifies the moment(s) atwhich a collection point is serviced and the volumecollected per visit. The foremost ways to determinethe moment of collection are as follows.

(1) Periodic schedules. A periodic schedule is asubset of periods (days) chosen from a baseset of consecutive periods, which is repeat-edly used. Typically, the collector can ini-tially determine the actual visit periods to beincluded in the schedule. Once specified,however, visits routinely have to occur duringthese periods.

(2) By monitoring demand. Smart drop-off sitesmonitor the generation rate, and the infor-mation is used to insert visits just in time, toprevent overspill, in a dynamic route-plan-ning model.

(3) Call services. For collections from staffeddrop-off sites, visits may be triggered by a callfrom the collection point. The collector mayspecify that a minimum quantity of productsshould be available before the call is made. Ina call service with periodic collection, thecollector will plan the visit in the next timeperiod that is part of a pre-arranged periodicschedule for the geographic area to which thecollection point belongs. In the call servicewith a timely collection guarantee, the col-lector assigns the visit to a period at will, butensures collection before a predefined timehas elapsed from the moment of the call.

(4) Triggered by a distribution schedule. If theintegration of collection and delivery isallowed (see also the next section on combi-nation level), the moment of collection couldbe triggered by a distribution schedule for thecustomer at the collection point itself or for acustomer at a location in its neighbourhood.

As for the volume collected per visit, it is standardpractice that all goods are collected. The exceptionoccurs when the vehicle has reached its capacity.In that case, the remaining products are eithercollected (by another vehicle) shortly after orduring the next scheduled visit.

5.2.3. Combination levelServices related to different classes of flows ofgoods can be combined in various ways.

(1) Separate routing of independent resources. Adedicated fleet of single compartment vehiclescollects one (possibly heterogeneous) flow ofgoods.

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(2) Separate routing of shared resources. Twoor more classes of flows are collected eitherwith the same crew or by the same set ofvehicles, or both, but in any case differentclasses are never in the same vehicle at anypoint in time. The vehicle is dispatched tocollect one class and it can only be assignedto a different class after unloading at thedepot (and possible cleaning and setup ofthe vehicle).

(3) Co-collecting source-separated flows of goods.Two or more classes are collected simulta-neously, hence two products of different clas-ses are allowed in the vehicle. Multi-compartment vehicles are often needed forpractical purposes (see next section on vehicletype).

(4) Integrating collection and delivery tasks. Themost common ways are mixing, backhauling,and partial mixing. Mixing is the situation inwhich deliveries and collections can bemade atrandom as long as the vehicle’s capacity con-straint is respected. A vehicle therefore cancollect before all deliveries have been made,resulting in amixed load. Customerswith botha delivery and collection request may requireonly a single visit. Mixing is not alwaysapplicable. First, laws may prohibit mixingcertain new and end-of-life products. Second,delivering new products can take priority overcollecting old ones. It may be unacceptable topostpone a delivery as a consequence of(unexpected) delays caused by previouslymade collections. Finally, vehicles are oftenrear loaded, hence the on-board load rear-rangement required by mixing might be diffi-cult, or even impossible, to carry out atcustomer locations. In those cases, backhaul-ing is an alternative. Backhauling means thatthe vehicle makes all its deliveries before anycollection can be made. Partial mixing is theapproachwheremixing is only possible if thereis enough shuffling space in the vehicle. Ingeneral, a feasible route looks as follows. The(full) vehicle starts with deliveries until thevolume occupied by loaded cargo is reduced toa certain level. From this point onward, mix-ing is allowed, provided that this level is notexceeded. When all deliveries are made, col-lected goods can fill the vehicle up to its normalcapacity.

5.2.4. Vehicle typeFinally, the characteristics of the collection vehi-cles have to match the collection infrastructure,policy, and combination level. Different truckdesigns and assorted collection equipment aredescribed by Graham (2001). There are tworemarks of importance in the context of systemdesign. First, more and more multi-compartmentvehicles become available. Traditional collectionvehicles have a single compartment and may beequipped with a compaction mechanism. Recentco-collection vehicles are flexible in number andrelative size of compartments, or in the compac-tion rate of different compartments. Dual-com-partment vehicles for example, can co-collect twoclasses, e.g. refuse and recyclables, refuse and yardtrimmings, or two streams of recyclables. Second,vehicles focusing on the integration of collectionswith deliveries are made more accessible than thetraditional rear loaders by means of tailgates at thesides, possibly in combination with a conveyor beltcovering the full length of the truck’s floor.

5.3. Features of vehicle routing models for productrecovery

What are the typical features that may be neededor encountered in vehicle routing models forreverse logistics?

(1) More freedom. The distribution policy in a‘‘traditional’’ supply chain context is typi-cally customizable. The benefits of personal-ized delivery outweigh the additional logisticscost. But an old returned product does notrepresent a capital cost to the generators orretailers, and there is no such thing as thethreat of a ‘‘lost sale’’ for the retailer if thecollector chooses, within some limits, thecollection moment. As a result, retailers andgenerators can more easily agree on a stan-dard policy if this keeps the bill low. In par-ticular, the absence of customer-specific timeconstraints, visit schedules, and/or bin-pack-ing effects (see ‘‘allowing split collection’’below), results in routes that are less likely tooverlap. Each vehicle will collect in its owngeographical zone. The following modellingfeatures may be encountered.

(2) Demand on nodes and arcs. In distributionsettings, typically, demand can be modelledas being located on the nodes of a network,

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i.e. the extreme points of the arcs. Each arcbetween two demand nodes represents theshortest or cheapest set of roads connectingthese two delivery locations. In some reverselogistics settings, e.g. kerbside collection ofrecyclables, demand may be better modelledas being continuously distributed along(some of) the arcs of a (road) network, giventhe many stops per vehicle tour.

(3) Allowing split collection. As a rule, splitdelivery is not allowed in the ‘‘traditional’’distribution models, i.e. the total demand of acustomer must be delivered in one single visit.Vehicle routing models hence need to copewith bin packing constraints that may inter-fere with the minimum distance objective,especially when there are large demands rel-ative to the vehicle capacity. In reverselogistics, split collection is more oftenallowed on the condition that the accumula-tion capacity of the collection infrastructureis taken into account.

(4) Multiple vehicle types. Professional collec-tors deploy a mixture of several vehicletypes, different in number of compart-ments, capacity, multi-mode capabili-ties, compaction mechanisms, and/or(un)loading mechanisms. The vehicle routingmay involve deciding which vehicle to use forwhich collection tasks (vehicle fleet mixproblems).

(5) Combining multiple inbound and outboundflows. The acquisition of low-value flows ofgoods from a large number of sourcesrequires the use of a low-cost system and,obviously, increasing the combination levelcan help achieve this objective. The vehiclerouting models thus need to be able to copewith the various combination approachesdescribed in Section 5.2.3.

(6) Supply uncertainty. As often mentioned in theliterature, the availability in timing and vol-ume of used products is, in general, moredifficult to predict than in a distributioncontext. Stochastic vehicle routing techniquesapply. In perhaps the simplest way, however,robustness can be obtained by artificiallyreducing the collection capacity of the vehiclefor the planning of the routes. For refusecollection, the compaction mechanism can be‘‘abused’’ to collect a little more than fore-

seen. Split collection may also be a means toavoid extra vehicle trips.

(7) Multi-period models. In distribution settings,customer-specific time windows or narrowtransport time windows arise frequently. In atypical reverse logistics context, the timewindows are not that extremely small, and forlow-value products the time span covers typ-ically more than a few days. To exploit theoption of postponement of collection to laterworkdays (periods), multi-period vehiclerouting models have to be used. The featuresmentioned above may be encountered here aswell. In addition to these are the following.

� Collection policy. Multi-period vehicle routingmodels are needed for the various collectionpolicies specified in Section 5.2.2.

� Minimizing the fixed cost. In some reverselogistics settings, sizable investments in spe-cialized vehicles or manpower require the con-sideration of fixed costs as well as variable(routing) costs. In particular, for the design ofthe collection policy and for solving the multi-period routing problem, the maximum numberof vehicles simultaneously deployed over theplanning horizon is to beminimized.While fixedcosts obviously are also of importance in dis-tribution settings, it is generally easier andcheaper to rent common vehicles or hire com-mon carriers in peak periods.

5.4. Some findings related to household refusecollection

Collecting refuse or recyclables from households incities is typically organized by splitting the serviceregion into several sectors and for each sectorspecifying the particular days on which a collectionoccurs. This sector design is firstly used to balancethe workload of the vehicles between the workdaysin order to minimize the fleet size. Secondly, itshould also allow for an efficient daily routing of thecollection vehicles. Research by Beullens (2001)indicates that the sector design, although having alarge impact on how well the workload between theworkdays is balanced, is not significantly affectingthe routing cost over a longer period of time. Thisinsensitivity to sector design supports a hierarchicalsolution approach which makes the problem easierto handle andmore attractive. In a first stage, sectordesign models need to especially look at workload

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balancing, i.e. minimizing the fleet size by deter-mining an optimal set of sectors and their periodicschedules. In a second stage, single-period vehiclerouting models can then be used to determine theindividual vehicle routes within each sector. Sectordesign models have been proposed by Beullens(2001).

It is also found that the routing cost is a linearfunction in the collection frequency f, all elseequal, of the form C1 + C2 f, where Ci (i ¼ 1, 2)represents a constant. The collection frequencytherefore has a considerable impact on the collec-tion cost. Furthermore, for the case refuse ishomogenously distributed between n points in aservice region of area A, vehicle capacity is Wv,and W amount of refuse is daily produced in theservice region, the routing cost can be character-ized as follows (Beullens et al. 2004):

C1WWmþ f ðC2

ffiffiffiffiffiffi

Anp

þ C3nÞ:

This dependence on n partially explains why kerb-side collection is more expensive than the collectionfrom drop-off sites or municipal depots where,obviously, a part of the cost for travelling and(un)loading is on account of the households. Usu-ally, the cost difference is even worse since kerbsidecollection needs a higher collection frequency todeal with the limited accumulation capacity of asingle household. Another cost disadvantage ofkerbside collection is related to the flexibility in thevisit schedule design. This means that collectionfrequencies in kerbside collection programs gener-ally require a stable and predictable schedule, whilethe collection from drop-off sites, and especiallyfrom municipal depots, can be organized morearbitrarily, i.e. on the moment the container hasreached its capacity. Kerbside collection is, how-ever, often still used.One aspect thatmay play a rolein this trade-off is that kerbside collection typicallyrealizes higher capture rates, i.e. more recyclablesare separately collected and removed from therefuse stream. From an overall perspective, highercapture rates may hence be favourable since thismay lead to increasing recycling rates.

The routing cost, however, becomes animportant factor for sector design when planningfor the co-collection of two flows toward the samedepot. In Beullens et al. (2004), it is shown how toestimate the effect on total cost when a source

separation program (see Section 5) is introduced,and how to design sectors. Using optimal sectordesigns for both situations, before and after theintroduction of source separation, the cost caneither increase or decrease. This largely depends onthe choice of collection frequencies and the level ofcombination (independent routing in single-com-partment vehicles, sharing single-compartmentvehicles, or co-collection in two-compartmentvehicles, see Section 5.2). In all investigated cases,however, a good sector design makes co-collectionthe lowest cost approach.

In particular, analysis indicates that the weeklyco-collection of two streams is about 10% cheaperin routing cost than the weekly collection of onestream and separately collecting the other streamevery two weeks. It is therefore somehow surpris-ing to see the latter scenario occurring in practice.Reasons for this can be (1) many single-compart-ment vehicles are still in use and a change to dual-compartment vehicles is expensive; (2) a dual-compartment vehicle needs to be flexible to adjustthe relative compartment size to the local capturerate observed during its tour, otherwise one com-partment might be full sooner than the other,decreasing collection efficiency; and (3) both col-lection tasks are outsourced to different organi-zations. The latter, combined with theconsideration of a specific depot for each organi-zation, will tend to decrease the value of co-col-lection, as indicated by some preliminary analysisin Beullens et al. (1999).

5.5. Some findings about the integration withdistribution

Another way to combine several flows of goods isto integrate the collection and distribution activi-ties, by means of backhauling or mixing (intro-duced in Section 5.2).

Figure 5 illustrates the general situation. Vehi-cles are located at a depot. Products need to bedelivered from a depot to several customers. At thesame time, (used) products need to be collectedfrom (other) customers and transported back tothe depot. Each request is a fraction of the vehi-cle’s capacity (less-than-truckload). The situationrepresents, for example, the delivery and take-backof photo copiers from business customers or therecently growing use of .75 m3 reusable metal

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containers – replacing one-way wooden containers– for the transportation of heavy intermediatecomponents between a supplier and industrialcustomers.

Some insights obtained by Beullens et al.(2004) are described next. In general, it is shownin that integration can at most reduce thetotal distance travelled by 50%, compared to sep-arately organizing the delivery and collection.Examples, with particular well-chosen locationsand demand sizes, can easily be constructed wherethe savings are either 0 or 50%, for mixing as wellas for backhauling.

Consider the situation where many customersare independently drawn from an identical distri-bution over a bounded service region of theEuclidean plane. Then more specific insights areobtained from an asymptotic probabilistic analy-sis. It appears that a determining factor is thenumber of vehicles needed. When the vehicle

capacity grows with the number of customers nsuch that all delivery demands and all collectiondemands can be serviced separately by a singlevehicle, backhauling is asymptotically as ‘‘ineffi-cient’’ as separate routing, while mixing clearlyperforms better. How much better depends onhow delivery and collection requests are geo-graphically distributed. The result depends on twoparameters, b and c. The first parameter can bedefined as the ratio of collection requests in theregion to the number of delivery requests. Theparameter c is roughly defined as the ratio ofcollection requests that coincide with a deliveryrequests (so-called exchange customers) to thetotal number of delivery requests. Figure 6a showsthe relative distance reduction for this single-vehicle case between mixing and backhauling orbetween mixing and separating delivery and pick-up tours. The relative distance reduction,limn!1 DT=T ¼ limn!1ðTS � TM Þ=TM ¼ limn!1ðTB � TM Þ=TM = (with probability one)

limDTT¼ 1þ

ffiffiffibp�

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi1þ b� cp

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi1þ b� cp

whereTI is the total distance travelled under policy I(I ¼M, B, or S; M ¼ mixing, B ¼ Backhauling,S ¼ Separating). Mixing is most valuable when b islarger and c is closer to b. In the analysis, it is suf-ficient to consider situations where b £ 1 since theother case can be considered by changing the role ofcollection and delivery requests in the model.

The situation is different when the vehiclecapacity is fixed or does not grow sufficiently withthe number of points, so that the number ofvehicles needed also tends to infinity with the

de

de

co

s

depot

delivery

collection

service region

Figure 5. Spatial context of the delivery and collectionproblem.

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 10

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

mil

(

(

∆ Τ / Τ

ββ

ε = 2

ε = 1..67

ε == 0

ε = 1

(b)(a)

γ = β

γ = β / 2

γ = 0

Figure 6. Asymptotic gap between (a) mixing and backhauling or separating delivery and pickup tours, single-vehicle case; and (b)integrating and separating delivery and pickup tours, multi-vehicle case.

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number of points. Then backhauling becomes asefficient as mixing. The benefit of integrationcompared to separating delivery and collectiontours depends again on b but also on a parametere, which can be interpreted as the relative size of anaverage collection to an average delivery load. Thec parameter becomes irrelevant for this case.Figure 6b shows for this multi-vehicle case therelative distance reduction from mixing or back-hauling compared to separating delivery andpickup tours. Now, the relative distance reduction,limn!1 DT=T ¼ limn!1ðTS � TM Þ=TM ¼ limn!1ðTS � TBÞ=TB = (almost surely)

limDTT¼ min be;

1

be

� �

The integration of collection and distributionseems most valuable in these situations where theproduct be approaches 1.

Finally, it is worthwhile to mention that in thecase of integration, the proper matching of deliv-ery and collection frequencies has a considerableimpact on efficiency. In this context, Beullens et al.(2004) investigate the value of postponing pickupswhen they can be integrated with non-postponabledeliveries. They propose a model for the derivationof conditions that determine when postponementwill generate savings, how big these savings are,and how to calculate the optimal postponementlevel. The value of postponement demonstrated inthese models underlines the observed postpone-ment approaches in practice and stresses theimportance of developing multi-period vehiclerouting models with integration, models that arecurrently not available in the literature.

6. Conclusions

In this chapter, obstacles that may arise whenintroducing product recovery in the economiclandscape are being described, as well as theframeworks, models, and insights from recentresearch. In general, the obstacles can be related,on the one hand, to the discrepancies betweenproduct recovery and the strategic objectives of thefirm, and, on the other hand, to the (expected)difficulties related to the efficient and effectiveimplementation of the logistic process that is nee-ded to support the reuse and recycling activities.

First, a firm needs to establish if productrecovery activities will increase shareholderwealth. They need to consider if they (will) operateunder a waste stream or a market-drivenapproach, or a combination, and if they will out-source these activities or not. Other aspects of astrategic importance are marketing-related issues,including the importance of a green image and thepotential interaction with the sales of new prod-ucts, and aspects of product design, competition,coordination, and legislation.

Second, the operational planning of remanu-facturing and recycling facilities is typically dif-ferent than in the forward supply chain. Obstaclesare the uncertainty in the variety, quality, quan-tity, and timing of the returning products, and thenecessity for an efficient and effective reverselogistics network that collects the interestingproducts from the (end-) customer.

Third, the design of reverse logistics network iscomplicated by the needs to match supply anddemand and steer the incoming products of dif-ferent variety and quality effectively and efficientlyto the desired reprocessing facilities.

Finally, increasing reverse logistics flows fromthe disposer markets introduce new issues in theareas of collection and vehicle routing. Twoprominent differences with ‘‘traditional’’ distri-bution logistics are the usually low value of thegoods and the large degree of freedom in decidingthe moment and method of collection. The searchfor the lowest-cost approach leads to multi-periodvehicle routing models that need to includestrategies that combine the transport of multipleflows of goods. In particular, models for co-col-lecting separated waste streams and for integrat-ing delivery and collection activities are indemand.

These issues are, amongst others, importantand deserve further consideration in order todevelop the field of product recovery in a practicaleconomic context. More on economic and logisticaspects of product recovery can be found in thebook of Dekker et al. (2004).

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