A hybrid discrete particle swarm optimization for the traveling salesman problem

被引：0
|
作者：
Li, Xiangyong [1 ]
Tian, Peng [1 ]
Hua, Jing [1 ]
Zhong, Ning [1 ]
机构：
[1] Shanghai Jiao Tong Univ, Coll Econ & Management, Shanghai 200052, Peoples R China
来源：
SIMULATED EVOLUTION AND LEARNING, PROCEEDINGS | 2006年 / 4247卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents a hybrid discrete particle swarm optimization (HDPSO) for solving the traveling salesman problem (TSP). The HDPSO combines anew discrete particle swarm optimization (DPSO) with a local search. DPSO is an approach designed for the TSP based on the binary version of particle swarm optimization. Unlike in general versions of particle swarm optimization, DPSO redefines the particle's position and velocity, and then updates its state by using a tour construction. The embedded local search is implemented to improve the solutions generated by DPSO. The experimental results on some instances are reported and indicate HDPSO can be used to solve TSPs.
引用
收藏
页码：181 / 188
页数：8
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