Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
Principles of artificial intelligence
Principles of artificial intelligence
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Shortest paths algorithms: theory and experimental evaluation
Mathematical Programming: Series A and B
“The quickest transshipment problem”
Proceedings of the sixth annual ACM-SIAM symposium on Discrete algorithms
Polynomial time algorithms for some evacuation problems
SODA '94 Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms
Introduction to Linear Optimization
Introduction to Linear Optimization
Algorithms for Network Programming
Algorithms for Network Programming
Introduction to Algorithms
Shortest Path Algorithms: An Evaluation Using Real Road Networks
Transportation Science
Evacuation planning: a capacity constrained routing approach
ISI'03 Proceedings of the 1st NSF/NIJ conference on Intelligence and security informatics
Evacuation route planning: scalable heuristics
Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems
Vehicle Priority Selection Algorithm for Evacuation Planning
ICCSA '08 Proceeding sof the international conference on Computational Science and Its Applications, Part I
Time-Aggregated Graphs for Modeling Spatio-temporal Networks
Journal on Data Semantics XI
Evacuation Route Planning Algorithm: Longer Route Preferential
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
A scalable heuristic for evacuation planning in large road network
Proceedings of the Second International Workshop on Computational Transportation Science
Spatio-temporal network databases and routing algorithms: a summary of results
SSTD'07 Proceedings of the 10th international conference on Advances in spatial and temporal databases
KI'09 Proceedings of the 32nd annual German conference on Advances in artificial intelligence
An evacuation planner algorithm in flat time graphs
Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication
Agent-based modeling for household level hurricane evacuation
Winter Simulation Conference
A multi-valued discrete particle swarm optimization for the evacuation vehicle routing problem
ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part I
Time-Aggregated graphs for modeling spatio-temporal networks
CoMoGIS'06 Proceedings of the 2006 international conference on Advances in Conceptual Modeling: theory and practice
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
Understanding population displacements on location-based call records using road data
Proceedings of the Second ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data
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Evacuation planning is critical for numerous important applications, e.g. disaster emergency management and homeland defense preparation. Efficient tools are needed to produce evacuation plans that identify routes and schedules to evacuate affected populations to safety in the event of natural disasters or terrorist attacks. The existing linear programming approach uses time-expanded networks to compute the optimal evacuation plan and requires a user-provided upper bound on evacuation time. It suffers from high computational cost and may not scale up to large transportation networks in urban scenarios. In this paper we present a heuristic algorithm, namely Capacity Constrained Route Planner(CCRP), which produces sub-optimal solution for the evacuation planning problem. CCRP models capacity as a time series and uses a capacity constrained routing approach to incorporate route capacity constraints. It addresses the limitations of linear programming approach by using only the original evacuation network and it does not require prior knowledge of evacuation time. Performance evaluation on various network configurations shows that the CCRP algorithm produces high quality solutions, and significantly reduces the computational cost compared to linear programming approach that produces optimal solutions. CCRP is also scalable to the number of evacuees and the size of the network.