Priority-based genetic local search and its application to the traveling salesman problem

Jyh Da Wei*, D. T. Lee

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Genetic algorithms and genetic local search are population based general-purpose search algorithms. Nevertheless, most of combinatorial optimization problems have critical requirements in their definition and are usually not easy to solve due to the difficulty in gene encoding. The traveling salesman problem is an example that requires each node to be visited exactly once. In this paper, we propose a genetic local search method with priority-based encoding. This method retains generality in applications, supports schema analysis during searching process, and is verified to gain remarkable search results for the traveling salesman problem.

Original languageEnglish
Title of host publicationSimulated Evolution and Learning - 6th International Conference, SEAL 2006, Proceedings
PublisherSpringer Verlag
Pages424-432
Number of pages9
ISBN (Print)3540473319, 9783540473312
DOIs
StatePublished - 2006
Externally publishedYes
Event6th International Conference Simulated Evolution and Learning, SEAL 2006 - Hefei, China
Duration: 15 10 200618 10 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

Conference

Conference6th International Conference Simulated Evolution and Learning, SEAL 2006
Country/TerritoryChina
CityHefei
Period15/10/0618/10/06

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