A hybrid discrete particle swarm optimization for the traveling salesman problem

Xiangyong Li, Peng Tian, Jing Hua, Ning Zhong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

29 Scopus citations

Abstract

This paper presents a hybrid discrete particle swarm optimization (HDPSO) for solving the traveling salesman problem (TSP). The HDPSO combines a new 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.

Original languageEnglish (US)
Title of host publicationSimulated Evolution and Learning - 6th International Conference, SEAL 2006, Proceedings
PublisherSpringer Verlag
Pages181-188
Number of pages8
ISBN (Print)3540473319, 9783540473312
DOIs
StatePublished - 2006
Event6th International Conference Simulated Evolution and Learning, SEAL 2006 - Hefei, China
Duration: Oct 15 2006Oct 18 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4247 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th International Conference Simulated Evolution and Learning, SEAL 2006
Country/TerritoryChina
CityHefei
Period10/15/0610/18/06

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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