Genetic Algorithms for the Travelling Salesman Problem: A Review of Representations and Operators

P. Larranaga, C.M.H. Kuipers, R.H. Murga, I. Inza, S. Dizdarevic

Research output: Contribution to journalArticleAcademicpeer-review

561 Citations (Scopus)

Abstract

This paper is the result of a literature study carried out by the authors. It is a review of the different attempts made to solve the Travelling Salesman Problem with Genetic Algorithms. We present crossover and mutation operators, developed to tackle the Travelling Salesman Problem with Genetic Algorithms with different representations such as: binary representation, path representation, adjacency representation, ordinal representation and matrix representation. Likewise, we show the experimental results obtained with different standard examples using combination of crossover and mutation operators in relation with path representation.
Original languageEnglish
Pages (from-to)129-170
Number of pages42
JournalArtificial intelligence review
Volume13
DOIs
Publication statusPublished - 1999
Externally publishedYes

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