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	Hybrid particle swarm optimization for vehicle routing problem with multiple objectives
	Xu Jie ; Huang De-xian
	2010-05-06 ; 2010-05-06
关键词	Theoretical or Mathematical/ Pareto analysis particle swarm optimisation transportation vehicles/ hybrid particle swarm optimization vehicle routing multiple objectives mutation operator roulette-wheel selection Pareto set/ C1290H Systems theory applications in transportation C1180 Optimisation techniques
中文摘要	In order to solve the vehicle routing problem with time windows (VRPTW) with multiple objectives, a solution was proposed by combining particle swarm optimization (PSO) with mutation operator. In the solution, with the help of roulette-wheel selection and mutation operator, the discrete problem with multiple objectives could be converged to optimal Pareto set and equally distributed along Pareto curve. The random key was adopted to change from continuous particle position vectors to discrete solution vectors. And the method of relatively minimum distance was proposed to evaluate the Pareto muster. In addition, no-interval coding method was put forward to reduce invalid iteration. Result of the experiments showed that the algorithm was simple and effective.
语种	中文 ; 中文
出版者	Editorial Department of CIMS ; China
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/9507]
专题	清华大学
推荐引用方式 GB/T 7714	Xu Jie,Huang De-xian. Hybrid particle swarm optimization for vehicle routing problem with multiple objectives[J],2010, 2010.
APA	Xu Jie,&Huang De-xian.(2010).Hybrid particle swarm optimization for vehicle routing problem with multiple objectives..
MLA	Xu Jie,et al."Hybrid particle swarm optimization for vehicle routing problem with multiple objectives".(2010).

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