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Capacity Constrained Routing Algorithms for Evacuation Planning: A Summary of Results Speaker: Chen-Nien Tsai.

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Presentation on theme: "Capacity Constrained Routing Algorithms for Evacuation Planning: A Summary of Results Speaker: Chen-Nien Tsai."— Presentation transcript:

1 Capacity Constrained Routing Algorithms for Evacuation Planning: A Summary of Results Speaker: Chen-Nien Tsai

2 2006/10/302 Reference ► Qingsong Lu, Betsy George, and Shashi Shekhar, “ Capacity Constrained Routing Algorithms for Evacuation Planning: A Summary of Results, ” Advances in Spatial and Temporal Databases, Proceeding of 9th International Symposium on Spatial and Temporal Databases (SSTD'05), Angra dos Reis, Brazil, August 22-24, 2005. Capacity Constrained Routing Algorithms for Evacuation Planning: A Summary of Results Capacity Constrained Routing Algorithms for Evacuation Planning: A Summary of Results

3 2006/10/303 Outline ► Introduction ► Problem Formulation ► Proposed Approach  Capacity Constrained Route Planner (CCRP) ► Performance Evaluation ► Summary

4 2006/10/304 Introduction (1/4) ► Evacuation Planning is critical for numerous applications.  Disaster emergency management  Homeland defense preparation ► The goal is to produce evacuation plans that identify routes and schedules to evacuate affected populations to safety.

5 2006/10/305 Introduction (2/4) ► Traffic assignment-simulation approach  Uses traffic simulation tools.  May take a long time to complete a simulation. ► Route-schedule planning approach  Uses network flow and routing algorithms to produce origin-destination routes and schedules.  Many researcher use linear programming method to find the optimal solution.

6 2006/10/306 Introduction (3/4) ► Linear Programming Method  Can produce optimal solutions for evacuation planning.  It is useful for evacuation scenarios with moderate size networks.  It is not suitable for large network size. ► The complexity is

7 2006/10/307 Introduction (4/4) ► Heuristic routing and scheduling algorithms  Produce sub-optimal evacuation plan.  Reduce computational cost.  It is useful for evacuation scenarios with large size networks.  The authors proposed Capacity Constrained Route Planner ► The complexity is

8 2006/10/308 Outline ► Introduction ► Problem Formulation ► Proposed Approach  Capacity Constrained Route Planner (CCRP) ► Performance Evaluation ► Summary

9 2006/10/309 Problem Formulation (1/2) ► Input:  A transportation network with capacity constraints on nodes and edges, travel time on edges, the total number of evacuees and their initial locations, and locations of evacuation destinations. ► Output  An evacuation plan.

10 2006/10/3010 Problem Formulation (2/2) ► Objective:  Minimize the evacuation egress time.  Minimize the computation cost. ► Constraint:  Edge travel time preserves FIFO property.  Edge travel time reflects delays at intersections.  Limited amount of computer memory.

11 2006/10/3011 An Example

12 2006/10/3012 An Evacuation Plan

13 2006/10/3013 Outline ► Introduction ► Problem Formulation ► Proposed Approach  Capacity Constrained Route Planner (CCRP) ► Performance Evaluation ► Summary

14 2006/10/3014 CCRP 1. Searches for route R with the earliest destination arrival time. 2. Computes the actual amount of evacuees that will travel through route R. (affected by the available capacity of route R) 3. The algorithm continues to iterate until all evacuees reach destination.

15 2006/10/3015 CCRP

16 2006/10/3016

17 2006/10/3017 S0S0

18 2006/10/3018 The Complexity of CCRP ► We assume  n: the number of nodes  m: the number of edges  p: the number of evacuees ► The complexity of CCRP is

19 2006/10/3019

20 2006/10/3020 The comparison ► MRCCP is another heuristic algorithm.

21 2006/10/3021 Outline ► Introduction ► Problem Formulation ► Proposed Approach  Capacity Constrained Route Planner (CCRP) ► Performance Evaluation ► Summary

22 2006/10/3022 Experiment Design

23 2006/10/3023 We Want to Know... ► How does the number of evacuees affect the performance of the algorithms? ► How does the source nodes affect the performance of the algorithms? ► Are the algorithms scalable to the size of the network?

24 2006/10/3024 The Effect on the Number of Evacuees (1/3) # of nodes: 5000 # of source nodes: 2000

25 2006/10/3025 The Effect on the Number of Evacuees (2/3) # of nodes: 5000 # of source nodes: 2000

26 2006/10/3026 The Effect on the Number of Evacuees (3/3) ► CCRP produces high quality solutions with much less run-time than that of NETFLO. ► The run-time of CCRP is scalable to the number of evacuees.

27 2006/10/3027 The Effect on the Number of Source Nodes (1/3) # of nodes: 5000 # of evacuees: 5000

28 2006/10/3028 The Effect on the Number of Source Nodes (2/3) # of nodes: 5000 # of evacuees: 5000

29 2006/10/3029 The Effect on the Number of Source Nodes (3/3) ► The solution quality of CCRP is not affected by the number of source nodes. ► The run-time of CCRP is scalable to the number of source nodes.

30 2006/10/3030 Are the algorithms scalable (3/3) # of source nodes: 10 # of evacuees: 5000

31 2006/10/3031 Are the algorithms scalable (1/3) # of source nodes: 10 # of evacuees: 5000

32 2006/10/3032 Are the algorithms scalable (3/3) ► Given a fixed number of evacuees and source nodes, the solution quality of CCRP increase as the network size increases. ► The run-time of CCRP is scalable to the size of the network.

33 2006/10/3033 Outline ► Introduction ► Problem Formulation ► Proposed Approach  Capacity Constrained Route Planner (CCRP) ► Performance Evaluation ► Summary

34 2006/10/3034 Summary (1/2) ► Linear programming method  Can produce optimal solutions for evacuation planning.  The complexity is too high. ► Heuristic algorithms  Produce sub-optimal evacuation plan.  Reduce computational cost.

35 2006/10/3035 Summary (2/2) ► Capacity Constrained Route Planner (CCRP)  Produces high quality solution  Reduces the computational cost

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