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Biogeography-Based Optimization for the Traveling Salesman Problems

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CSO '10: Proceedings of the 2010 Third International Joint Conference on Computational Science and Optimization - Volume 01

Pages 295 - 299

https://doi.org/10.1109/CSO.2010.79

Published: 28 May 2010 Publication History

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Abstract

Biogeography-based optimization (BBO) is a novel evolutionary algorithm that is based on the mathematics of biogeography. In the BBO model, problem solutions are represented as islands, and the sharing of features between solutions is represented as immigration and emigration between the islands. This paper presents an application of the BBO algorithm to the traveling salesman problems. The BBO solution is compared with the solution of the same problem using the genetic algorithms (GA). The results of simulation indicate that BBO algorithm performs better than the GA in determining an optimal solution of the traveling salesman problems.

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Goudarzi SHassan WAnisi MKhan MSoleymani S(2018)Intelligent Technique for Seamless Vertical Handover in Vehicular NetworksMobile Networks and Applications10.1007/s11036-017-0979-623:6(1462-1477)Online publication date: 1-Dec-2018
https://dl.acm.org/doi/10.1007/s11036-017-0979-6
Xu QWang NZhang JGu X(2016)Enhancing the Performance of Biogeography-Based Optimization in Discrete DomainProceedings, Part I, of the 6th International Conference on Advances in Swarm and Computational Intelligence - Volume 914010.1007/978-3-319-20466-6_43(403-414)Online publication date: 25-Jun-2016
https://dl.acm.org/doi/10.1007/978-3-319-20466-6_43
García-Torres JDamas SCordón OSantamaría J(2014)A case study of innovative population-based algorithms in 3D modelingExpert Systems with Applications: An International Journal10.1016/j.eswa.2013.08.07441:4(1750-1762)Online publication date: 1-Mar-2014
https://dl.acm.org/doi/10.1016/j.eswa.2013.08.074
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Biogeography-Based Optimization for the Traveling Salesman Problems

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Published In

CSO '10: Proceedings of the 2010 Third International Joint Conference on Computational Science and Optimization - Volume 01

May 2010

493 pages

ISBN:9780769540306

Publisher

IEEE Computer Society

United States

Publication History

Published: 28 May 2010

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Goudarzi SHassan WAnisi MKhan MSoleymani S(2018)Intelligent Technique for Seamless Vertical Handover in Vehicular NetworksMobile Networks and Applications10.1007/s11036-017-0979-623:6(1462-1477)Online publication date: 1-Dec-2018
https://dl.acm.org/doi/10.1007/s11036-017-0979-6
Xu QWang NZhang JGu X(2016)Enhancing the Performance of Biogeography-Based Optimization in Discrete DomainProceedings, Part I, of the 6th International Conference on Advances in Swarm and Computational Intelligence - Volume 914010.1007/978-3-319-20466-6_43(403-414)Online publication date: 25-Jun-2016
https://dl.acm.org/doi/10.1007/978-3-319-20466-6_43
García-Torres JDamas SCordón OSantamaría J(2014)A case study of innovative population-based algorithms in 3D modelingExpert Systems with Applications: An International Journal10.1016/j.eswa.2013.08.07441:4(1750-1762)Online publication date: 1-Mar-2014
https://dl.acm.org/doi/10.1016/j.eswa.2013.08.074
Zheng YLing HShi HChen HChen S(2014)Emergency railway wagon scheduling by hybrid biogeography-based optimizationComputers and Operations Research10.1016/j.cor.2013.09.00243(1-8)Online publication date: 1-Mar-2014
https://dl.acm.org/doi/10.1016/j.cor.2013.09.002
Zheng YLing HWu XXue J(2014)Localized biogeography-based optimizationSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-013-1209-118:11(2323-2334)Online publication date: 1-Nov-2014
https://dl.acm.org/doi/10.1007/s00500-013-1209-1

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Hybrid biogeography-based evolutionary algorithms

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Two-stage update biogeography-based optimization using differential evolution algorithm (DBBO)

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