Particle swarm optimization based on the average optimal information for vehicle routing problem

被引：1
|
作者：
Li, Zhuangkuo [1 ]
Ma, Yannan [1 ]
机构：
[1] Guilin Univ Elect Technol, Sch Business, Guilin, Peoples R China
来源：
2013 SIXTH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID), VOL 1 | 2013年
关键词：
vehicle routing problem; particle swarm optimization; average optimal information; combination optimization;
D O I：
10.1109/ISCID.2013.20
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
According to the weakness of standard particle swarm optimization in dealing with vehicle routing problem (VRP), based on the definition of particle swarm optimization, this paper introduce the average information of individual and the global information to the standard PSO. A new hybrid form of PSO (AVGPSO), which is based on the mean information of individual optimal information and the global optimal information, is brought forward. This proposed algorithm is applied to VRP and compared with standard particle swarm optimization. The result shows that the proposed algorithm has better probability for solving VRP.
引用
收藏
页码：51 / 54
页数：4
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