1987international conference on Genetic algorithmsRequires access

A study of permutation crossover operators on the traveling salesman problem

I. M. Oliver, David J. Smith, J. R. C. Holland

Open publisher page 892 citations

Abstract

The application of Genetic Algorithms to problems which are not amenable to bit string representation and traditional has been a growing area of interest. One approach has been to represent solutions by permutations of a list, and crossover operators have been introduced to preserve legality of offspring. Three permutation crossovers are analyzed to characterize how they sample the o-schema space, and hence what type of problems they may be applicable to. Experiments performed on the Traveling Salesman Problem go some way to support the theoretical analysis.

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What this paper is about

The application of Genetic Algorithms to problems which are not amenable to bit string representation and traditional has been a growing area of interest. One approach has been to represent solutions by permutations of a list, and crossover operators have been introduced to preserve legality of offspring. Three permutation crossovers are analyzed to characterize how they sample the o-schema space, and hence what type of problems they may be applicable to. Experiments performed on the Traveling Salesman Problem go some way to support the theoretical analysis.

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Available abstract

The application of Genetic Algorithms to problems which are not amenable to bit string representation and traditional has been a growing area of interest. One approach has been to represent solutions by permutations of a list, and crossover operators have been introduced to preserve legality of offspring. Three permutation crossovers are analyzed to characterize how they sample the o-schema space, and hence what type of problems they may be applicable to. Experiments performed on the Traveling Salesman Problem go some way to support the theoretical analysis.

Key concepts: Travelling salesman problem, Crossover, Permutation (music), Computer science, Schema (genetic algorithms), Theoretical computer science, Mathematics, Mathematical optimization

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