期刊
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
卷 24, 期 3, 页码 517-525出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.engappai.2010.08.005
关键词
Evolutionary algorithm; Biogeography-based optimization; Constrained optimization
类别
资金
- Directorate For Engineering
- Div Of Civil, Mechanical, & Manufact Inn [0826124] Funding Source: National Science Foundation
Biogeography-based optimization (BBO) is a new evolutionary optimization method that is based on the science of biogeography. We propose two extensions to BBO. First, we propose a blended migration operator. Benchmark results show that blended BBO outperforms standard BBO. Second, we employ blended BBO to solve constrained optimization problems. Constraints are handled by modifying the BBO immigration and emigration procedures. The approach that we use does not require any additional tuning parameters beyond those that are required for unconstrained problems. The constrained blended BBO algorithm is compared with solutions based on a stud genetic algorithm (SGA) and standard particle swarm optimization 2007 (SPSO 07). The numerical results demonstrate that constrained blended BBO outperforms SGA and performs similarly to SPSO 07 for constrained single-objective optimization problems. (C) 2010 Elsevier Ltd. All rights reserved.
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