期刊
APPLIED MATHEMATICAL MODELLING
卷 41, 期 -, 页码 630-649出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.apm.2016.09.020
关键词
Biogeography-based optimization; Powell's method; Random ring topology; Artificial bee colony
资金
- National Natural Science Foundation of China [11401357]
- Natural Science Foundation of Guangxi Province [2014GXNSFBA118023, 2013GXNSFAA019003]
- Fangchenggang Scientific research and technology development plan [42]
- Program to Sponsor Teams for Innovation in the Construction of Talent Highlands in Guangxi Institutions of Higher Learning [2011147]
- Doctoral Research Fund of Guilin University of Technology
Biogeography-based optimization (BBO) is a competitive population optimization algorithm based on biogeography theory with inherently insufficient exploration capability and slow convergence speed. To overcome limitations, we propose an improved variant of BBO, named PRBBO, for solving global optimization problems. In PRBBO, a hybrid migration operator with random ring topology, a modified mutation operator, and a self-adaptive Powell's method are rational integrated together. The hybrid migration operator with random ring topology, denoted as RMO, is created by using local ring topology to replace global topology, which can avoid the asymmetrical migration operation and enhance potential population diversity. The self-adaptive Powell's method is amended by using self-adaptive parameters for suiting evolution process to enhance solution precision quickly. Extensive experimental tests are carried out on 24 benchmark functions to show effectiveness of the proposed algorithm. Simulation results were compared with original BBO, ABC, DE, other variants of the BBO, and other state-of-the-art evolutionary algorithms. Finally, the effectiveness of operators on the performance of PRBBO is also discussed. (C) 2016 Elsevier Inc. All rights reserved.
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