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Research of Biogeography-Based Multi-Objective Evolutionary Algorithm

Research of Biogeography-Based Multi-Objective Evolutionary Algorithm

Hongwei Mo, Zhidan Xu
Copyright: © 2013 |Pages: 11
ISBN13: 9781466636255|ISBN10: 1466636254|EISBN13: 9781466636262
DOI: 10.4018/978-1-4666-3625-5.ch010
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MLA

Mo, Hongwei, and Zhidan Xu. "Research of Biogeography-Based Multi-Objective Evolutionary Algorithm." Interdisciplinary Advances in Information Technology Research, edited by Mehdi Khosrow-Pour, D.B.A., IGI Global, 2013, pp. 125-135. https://doi.org/10.4018/978-1-4666-3625-5.ch010

APA

Mo, H. & Xu, Z. (2013). Research of Biogeography-Based Multi-Objective Evolutionary Algorithm. In M. Khosrow-Pour, D.B.A. (Ed.), Interdisciplinary Advances in Information Technology Research (pp. 125-135). IGI Global. https://doi.org/10.4018/978-1-4666-3625-5.ch010

Chicago

Mo, Hongwei, and Zhidan Xu. "Research of Biogeography-Based Multi-Objective Evolutionary Algorithm." In Interdisciplinary Advances in Information Technology Research, edited by Mehdi Khosrow-Pour, D.B.A., 125-135. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-3625-5.ch010

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Abstract

Biogeography-based optimization algorithm (BBO) is an optimization algorithm inspired by the migration of animals in nature. A new multi-objective evolutionary algorithm is proposed, which is called Biogeography-based multi-objective evolutionary algorithm (BBMOEA). The fitness assignment and the external population elitism of SPEA2 are adapted to ensure even distribution of the solution set. The population evolutionary operators of BBO are applied to the evolution of the external population to ensure the convergence of the solution set. Simulation results on benchmark test problems illustrate the effectiveness and efficiency of the proposed algorithm.

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