A particle swarm optimization for the vehicle routing problem with simultaneous pickup and delivery
作者： The Jin Ai , Voratas Kachitvichyanukul
DOI: 10.1016/J.COR.2008.04.003
关键词: Representation (mathematics) 、 Computer science 、 Benchmark (computing) 、 Swarm intelligence 、 Vehicle routing problem 、 Routing (electronic design automation) 、 Metaheuristic 、 Particle swarm optimization 、 Mathematical optimization 、 Evolutionary algorithm
摘要: This paper proposes a formulation of the vehicle routing problem with simultaneous pickup and delivery (VRPSPD) particle swarm optimization (PSO) algorithm for solving it. The is generalization three existing VRPSPD formulations. main PSO developed based on GLNPSO, multiple social structures. A random key-based solution representation decoding method proposed implementing VRPSPD. n customers m vehicles (n+2m)-dimensional particle. starts by transforming to priority list enter route matrix serve each customer. routes are constructed customer matrix. tested using benchmark data sets available from literature. computational result shows that competitive other published results Some new best known solutions also found method. Scope Purpose: applies real-value version (VRPSPD). reformulated generalized formulations in purposes this explain mechanism demonstrate effectiveness
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