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On the application of simple OR models to the Land Force. Peter J Dortmans , Stephen Bourn, Richard Egudo, Svetoslav Gaidow, Wayne Hobbs & Denis Shine Land Operations Division Defence Science & Technology Organisation Edinburgh, AUSTRALIA. Defining Simple Modelling Some Land Force examples - PowerPoint PPT Presentation
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On the application of simple OR models to the Land Force
Peter J Dortmans, Stephen Bourn, Richard Egudo, Svetoslav Gaidow, Wayne Hobbs &
Denis Shine
Land Operations Division
Defence Science & Technology Organisation
Edinburgh, AUSTRALIA
Summary
• Defining Simple Modelling
• Some Land Force examples
• Food for thought
• Defining Simple Modelling
• Some Land Force examples
• Food for thought
Simple Models
All models are wrong – some models are useful!
Occam’s Razor –models should be as simple as possible, but no simpler!
? What is a ‘simple model’?
Simple vs Detailed Models:A viewpoint
Axis Simple models Detailed models Catch Phrase “Doing the right problem” “Doing the problem right”
Purpose Exploration and Refinement Assessment and Evaluation Aim Develop understanding Compare options
Philosophy
Driver Immediacy Precision Prior information Limited Detailed Typical Problem Ill-defined Well understood
Problem Space
Degrees of freedom Many Few Efficiency Metric Responsiveness Accuracy Deliverables Insights Answers
Solution Space
Effectiveness Metric Viability Validity
• Defining Simple Modelling
• Some Land Force examples
• Food for thought
Combat ID
? Question: What advantages do CID give?
Technique: Modified Lanchester
Combat ID -Data
)( AfaBbdt
dA )( BfbAa
dt
dB
Force Attrition coefficient Fratricide coefficient
A without CID a=0.6 fa=0.1
A with CID a=0.4 fa=0.02
B b=0.4 fb=0.1
fa and fb are fratricide coefficients
Combat ID - Results
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.90
1
2
3
4
5
6
7
8
9
10
w/out CIDwith CID BA
A
0 .45 0 .4 7 5 0.7 2
B
A
dA
dBB
A
dA
dB 1,max
Combat ID - Results
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.90
1
2
3
4
5
6
7
8
9
10
w/out CIDwith CID BA
A
0 .45 0 .4 7 5 0.7 2
B
A
dA
dBB
A
dA
dB 1,max
Initial state End state
Without CID With CID
00
0
BA
A
A0 B0
A B A B
0.231 0.3 1.0 0.0 0.858 0.0 0.877
0.375 0.6 1.0 0.0 0.558 0.0 0.642
0.459 0.85 1.0 0.158 0.0 0.0 0.254
0.769 1.0 0.3 0.919 0.0 0.941 0.0
Combat ID
? Question: What advantage do CID give?
Technique: Modified Lanchester
Better: Is CID always an advantage?
Minimise all blue casualties
vs minimise blue fratricide casualties
Tactical Effects
? Problem: Land forces in 2025?
Technique: Agent-based distillations
Explore problem space
o Create “conceptual forces” based on:• Engagement, Information Collection,
Communication, Decision Making, Sustainment, Movement, Protection
Tactical Effects – MANA simulation• e.g. Envelopment
– On contact: back away, fan out, then attacks
– Focus: Information Collection, Decision Making and Movement
Tactical Effects – MANA simulation
Default Scenario Envelopment Succeeding Envelopment Failing
• e.g. Envelopment
– On contact: back away, fan out, then attacks
– Focus: Information Collection, Decision Making and Movement
Tactical Effects - Observations
Tactical Effects - Observations
Tactical Effects
? Problem: Land forces in 2025?
Outcomes Areas of impact Synergies and antagonisms Emergent Behaviour Basis for further studies
Risk Management Matrix
? Comparing future force structures - 2015
What can go wrong? & What can get better?
Risk Management Matrix
NEGATIVE CONSEQUENCES POSITIVE CONSEQUENCES
-5 -4 -3 -2 -1 LIKELIHOOD
1 2 3 4 5 E E H H M ALMOST
CERTAIN
M
H H E E
E E H M M
LIKELY M M H E E
E H M M L POSSIBLE
L M M H E
H H M L L UNLIKELY
L L M H H
H M L L L RARE
L L L M H
Risk Management Matrix
? Comparing future force structures - 2015
What can go wrong? & What can get better?
SME input – AHP facilitated
Risk Management Matrix
NEGATIVE CONSEQUENCES POSITIVE CONSEQUENCES
-5 -4 -3 -2 -1 LIKELIHOOD
1 2 3 4 5 E E H H M ALMOST
CERTAIN
M
H H E E
E E H M M
LIKELY M M H E E
E H M M L POSSIBLE
L M M H E
H H M L L UNLIKELY
L L M H H
H M L L L RARE
L L L M H
-5 -4 -3 -2 -1 1 2 3 4 5E E H H M M H H E E
E E H M M M M H E E
E H M M L L M M H E
H H M L L L L M H H
H M L L L L L L M H
RARE
ALMOST CERTAIN
LIKELY
POSSIBLE
UNLIKELY
NEGATIVE CONSEQUENCES LIKELIHOOD POSITIVE CONSEQUENCES
Risk Management Matrix
? Comparing future force structures - 2015
What can go wrong? & What can get better?
SME input – AHP facilitated
Relative merits of forces and issues/risks
Asymmetric Conflict
? Problem: Adapting conventional forces to asymmetric threats
Techniques: Conceptual Modelling; SME input; Pair-wise comparisons
Asymmetric Conflict:
Asymmetric Conflict: Conceptual Model
Asymmetric Conflict Average Scores AAAS Descriptor Characteristic Blue Red
Secure 3.6 1.8 Communication Non-Secure 3.0 3.8 Precision 2.6 2.8 Engagement Non-Precision 3.4 1.8 Tactical 3.4 2.4 Movement Operational 3.8 3.0 HUMINT 1.8 3.6 Information
Collection SIGINT 3.8 1.6 Military 3.8 1.6 Sustainment Local 2.4 3.8 Physical 3.4 1.8 Protection Concealment 2.8 3.6 Tactical 3.4 3.4 Decision Making Operational 3.2 2.8
Asymmetric Conflict Average Scores AAAS Descriptor Characteristic Blue Red
Secure 3.6 1.8 Communication Non-Secure 3.0 3.8 Precision 2.6 2.8 Engagement Non-Precision 3.4 1.8 Tactical 3.4 2.4 Movement Operational 3.8 3.0 HUMINT 1.8 3.6 Information
Collection SIGINT 3.8 1.6 Military 3.8 1.6 Sustainment Local 2.4 3.8 Physical 3.4 1.8 Protection Concealment 2.8 3.6 Tactical 3.4 3.4 Decision Making Operational 3.2 2.8
Enhance HUMINT
Reduce Local Support
Asymmetric Conflict
? Problem: Adapting conventional forces to asymmetric threats
Techniques: Conceptual Modelling; SME input; Pair-wise comparisons
Indicate opportunities & threats
• Defining Simple Modelling
• Some Land Force examples
• Food for thought
Food for thought
• Simple models – scope problem– raise questions– set boundaries
• How do we assess their ‘goodness’?
• How do we manage ‘complexity’?
• How do we make sure they are used appropriately?
Questions