An Adaptive Mutation Multi-particle Swarm Optimization for Traveling Salesman Problem

被引：0

作者：

Gao, Ming-fang ^{[1
]}

Fu, Xue-liang ^{[1
]}

Dong, Gai-fang ^{[1
]}

Li, Hong-hui ^{[1
]}

机构：

[1] Inner Mongolia Agr Univ, Coll Comp & Informat Engn, Hohhot 010018, Peoples R China

来源：

PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON MATERIAL, MECHANICAL AND MANUFACTURING ENGINEERING | 2015年 / 27卷

关键词：

Particle Swarm Optimization; Adaptive mutation; Multi-particle swarm; Traveling Salesman Problem;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Traveling Salesman Problem (TSP) is a well-known NP-hard combinatorial optimization problem. The Particle Swarm Optimization has been proven to succeed in lots of problems, but the PSO algorithm is challenging due to a variety of factors such as easy to fall into local optimal solution and the convergence speed is slow in the later. In this paper, we propose an adaptive mutation multi-particle swarm optimization algorithm (AMPSO) to the TSP. The experimental results show that the proposed algorithm can achieves better performance compared to the standard PSO method to solve the TSP.

引用

页码：1003 / 1006

页数：4

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