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

DOI

10.2991/ic3me-15.2015.194How to use a DOI?

Keywords

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

Abstract

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.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Mingfang Gao
AU  - Xueliang Fu
AU  - Gaifang Dong
AU  - Honghui Li
PY  - 2015/08
DA  - 2015/08
TI  - An Adaptive Mutation Multi-particle Swarm Optimization for Traveling Salesman Problem
BT  - Proceedings of the 3rd International Conference on Material, Mechanical and Manufacturing Engineering
PB  - Atlantis Press
SP  - 1003
EP  - 1007
SN  - 2352-5401
UR  - https://doi.org/10.2991/ic3me-15.2015.194
DO  - 10.2991/ic3me-15.2015.194
ID  - Gao2015/08
ER  -