Contraflow network reconfiguration for evacuation planning: a summary of results
Proceedings of the 13th annual ACM international workshop on Geographic information systems
Capacity constrained routing algorithms for evacuation route planning
Capacity constrained routing algorithms for evacuation route planning
Solving shortest path problem using particle swarm optimization
Applied Soft Computing
Contraflow Transportation Network Reconfiguration for Evacuation Route Planning
IEEE Transactions on Knowledge and Data Engineering
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
IEEE Transactions on Intelligent Transportation Systems
Solving vehicle assignment problem using evolutionary computation
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part I
Capacity constrained routing algorithms for evacuation planning: a summary of results
SSTD'05 Proceedings of the 9th international conference on Advances in Spatial and Temporal Databases
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Flood evacuation operations face a difficult task in moving affected people to safer locations. Uneven distributions of transport, untimely assistance and poor coordination at the operation level are among the main problems in the evacuation process. This is attributed to the lack of research focus on evacuation vehicle routing. This paper proposes an improved discrete particle swarm optimization (DPSO) with a random particle priority value and decomposition procedure as a searching strategy to solve evacuation vehicle routing problem (EVRP). The search strategies are proposed to reduce the searching space of the particles to avoid local optimal problem. This algorithm was computationally experimented with different number of potentially flooded areas, various types of vehicles, and different speed of vehicles with DPSO and genetic algorithm (GA). The findings show that an improved DPSO with a random particle priority value and decomposition procedure is highly competitive. It offers outstanding performance in its fitness value (total travelling time) and processing time.