Genetic algorithm solution of the TSP avoiding special crossover and mutation

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Ucoluk G.

INTELLIGENT AUTOMATION AND SOFT COMPUTING, vol.8, no.3, pp.265-272, 2002 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 8 Issue: 3
  • Publication Date: 2002
  • Doi Number: 10.1080/10798587.2000.10642829
  • Journal Name: INTELLIGENT AUTOMATION AND SOFT COMPUTING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.265-272
  • Keywords: genetic algorithms, permutation representation, traveling salesman problem, crossover, partially mapped crossover, PMX, TSP, OPTIMIZATION, EVOLUTION
  • Middle East Technical University Affiliated: Yes

Abstract

Ordinary representations of permutations in Genetic Algorithms (GA) is handicapped with producing offspring which are not permutations at all. The conventional solution for crossover and mutation operations of permutations is to device 'special' operators. Unfortunately these operators suffer from violating the nature of crossover. Namely, considering the gene positions on the chromosome, these methods do not allow n-point crossover techniques which are known to favour building-block formations. In this work, an inversion sequence is proposed as the representation of a permutation. This sequence allows repetitive values and hence is robust under ordinary (n-point) crossover. There is a one-to-one mapping from ordinary permutation representation to the inversion sequence representation.