Delft University of Technology – Erasmus University Rotterdam University of Twente – Radboud University Nijmegen
University of Groningen
Operational Transport Planning with Incidents
Experiments with Traplas
Jonne Zutt and Cees WitteveenFaculty of EEMCS
TRAIL Congress 2006
www.rstrail.nl
Operational Transport Planning with Incidents• Operational Planning for the Pickup
and Delivery Transportation problem
• Approach
• Research questions• Operational Planning Methods
• Experiments
• Future work
Contents
Problem
Methods
Experiments
Future work
TRAIL Congress 2006
www.rstrail.nl
Problem description
• Pickup and Delivery Transportation Problem: Freight has to be transported from a source to a destination location respecting specified time intervals on a transport network with limited capacities and speeds.
• Limited capacities lead to conflicts.
Contents
Problem
Methods
Experiments
Future work
TRAIL Congress 2006
www.rstrail.nl
Approach
• Multi-agent system, where the agents are vehicle planners, crossroad agents, customers, auctioneers, etc.
• TRAPLAS: based on Pamela’s RTL, a discrete event simulation kernel [vanGemund].
• Linking experimental results to theory and use results to discover new relations.
Contents
Problem
Methods
Experiments
Future work
TRAIL Congress 2006
www.rstrail.nl
Research questions
• What information is necessary to obtain efficient planning methods (collaboration vs competition)?
• What happens when varying workload, number of agents (scalability), incident level (normal to extreme circumstances, robustness)?
• What is the relation between performance and characteristics of the transport network?
Contents
Problem
Methods
Experiments
Future work
TRAIL Congress 2006
www.rstrail.nl
Application
• AGV terminals (ECT)
• Underground logistic system (OLS)
• Inland shipping
• Taxiway routing
Contents
Problem
Methods
Experiments
Future work
TRAIL Congress 2006
www.rstrail.nl
Planning methods
• Uninformed: not aware of plans of other agents.
• Informed: planning around reservations of other agents.
• Revising priority: reconsidering precedences on crossroads.
• Revising routes: reconsidering routes.
Contents
Problem
Methods
Experiments
Future work
TRAIL Congress 2006
www.rstrail.nl
Planning methods
r1 r3
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Problem
Methods
Experiments
Future work
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TRAIL Congress 2006
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Uninformed planning
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5Σ 15
Contents
Problem
Methods
Experiments
Future work
TRAIL Congress 2006
www.rstrail.nl
Informed planning
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Contents
Problem
Methods
Experiments
Future work
TRAIL Congress 2006
www.rstrail.nl
Revising priorities
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9
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6Σ 20
Contents
Problem
Methods
Experiments
Future work
TRAIL Congress 2006
www.rstrail.nl
Revising routes
r1 r3
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5
6Σ 18
Contents
Problem
Methods
Experiments
Future work
TRAIL Congress 2006
www.rstrail.nl
Experiments
• 8x8 grid networks• 32 transport agents• Workload varies from 160 to
approx. 1000 transportation orders• Incident level varies from normal
(no incidents) to severe (failure probability 0.1) circumstances
Contents
Problem
Methods
Experiments
Future work
TRAIL Congress 2006
www.rstrail.nl
Increasing workload
Contents
Problem
Methods
Experiments
Future work
TRAIL Congress 2006
www.rstrail.nl
Groups of agents
200 400 600 800
-0.3
-0.2
-0.1
0.0
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Topology: grid
Workload (numb$r of transportation ord$rs)
W$l
far$
_Gro
up_1
024
Informed
Uninformed
Revising routes (order profits)
Contents
Problem
Methods
Experiments
Future work
TRAIL Congress 2006
www.rstrail.nl
Increasing level of incidents
Contents
Problem
Methods
Experiments
Future work
TRAIL Congress 2006
www.rstrail.nl
Future work
• Verifying theoretical results on collaboration and congestion games
• Add planning methods (variants)
• Experimenting with transport network topologies
• Inland shipping
Contents
Problem
Methods
Experiments
Future work
TRAIL Congress 2006
www.rstrail.nl
Questions?
?Contents
Problem
Methods
Experiments
Future work
TRAIL Congress 2006
www.rstrail.nl
Modeling conflicts
Contents
Problem
Methods
Experiments
Future work