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

Authors:
P. Larrañaga;C. M. H. Kuijpers;R. H. Murga;I. Inza;S. Dizdarevic
Affiliations:
Dept. of Computer Science and Artificial Intelligence, University of the Basque Country, P.O. Box 649, E-20080 San Sebastián, The Basque Country, Spain E-mail: ccplamup@si.ehu.es;Dept. of Computer Science and Artificial Intelligence, University of the Basque Country, P.O. Box 649, E-20080 San Sebastián, The Basque Country, Spain E-mail: ccplamup@si.ehu.es;Dept. of Computer Science and Artificial Intelligence, University of the Basque Country, P.O. Box 649, E-20080 San Sebastián, The Basque Country, Spain E-mail: ccplamup@si.ehu.es;Dept. of Computer Science and Artificial Intelligence, University of the Basque Country, P.O. Box 649, E-20080 San Sebastián, The Basque Country, Spain E-mail: ccplamup@si.ehu.es;Dept. of Computer Science and Artificial Intelligence, University of the Basque Country, P.O. Box 649, E-20080 San Sebastián, The Basque Country, Spain E-mail: ccplamup@si.ehu.es
Venue:
Artificial Intelligence Review
Year:
1999

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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.