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Solving Travelling Salesman Problem with an Improved Hybrid Genetic Algorithm

Lin, Bao Lin; Sun, Xiaoyan; Salous, Sana

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Authors

Bao Lin Lin

Xiaoyan Sun



Abstract

We present an improved hybrid genetic algorithm to solve the two-dimensional Euclidean traveling salesman problem (TSP), in which the crossover operator is enhanced with a local search. The proposed algorithm is expected to obtain higher quality solutions within a reasonable computational time for TSP by perfectly integrating GA and the local search. The elitist choice strategy, the local search crossover operator and the double-bridge random mutation are highlighted, to enhance the convergence and the possibility of escaping from the local optima. The experimental results illustrate that the novel hybrid genetic algorithm outperforms other genetic algorithms by providing higher accuracy and satisfactory efficiency in real optimization processing.

Citation

Lin, B. L., Sun, X., & Salous, S. (2016). Solving Travelling Salesman Problem with an Improved Hybrid Genetic Algorithm. Journal of Computer and Communications, 4(15), 98-106. https://doi.org/10.4236/jcc.2016.415009

Journal Article Type Article
Acceptance Date Nov 25, 2016
Online Publication Date Nov 28, 2016
Publication Date Nov 28, 2016
Deposit Date Feb 14, 2017
Publicly Available Date May 8, 2017
Journal Journal of Computer and Communications
Print ISSN 2327-5219
Electronic ISSN 2327-5227
Publisher Scientific Research Publishing
Peer Reviewed Peer Reviewed
Volume 4
Issue 15
Pages 98-106
DOI https://doi.org/10.4236/jcc.2016.415009

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