Bao Lin Lin
Solving Travelling Salesman Problem with an Improved Hybrid Genetic Algorithm
Lin, Bao Lin; Sun, Xiaoyan; Salous, Sana
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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Copyright Statement
Copyright © 2016 by authors and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY 4.0).http://creativecommons.org/licenses/by/4.0/
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