期刊
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
卷 16, 期 3, 页码 339-353出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TEVC.2011.2161091
关键词
Chemical reaction optimization; continuous optimization; metaheuristics
资金
- Strategic Research Theme of Information Technology of University of Hong Kong
- Croucher Foundation
Optimization problems can generally be classified as continuous and discrete, based on the nature of the solution space. A recently developed chemical-reaction-inspired metaheuristic, called chemical reaction optimization (CRO), has been shown to perform well in many optimization problems in the discrete domain. This paper is dedicated to proposing a real-coded version of CRO, namely, RCCRO, to solve continuous optimization problems. We compare the performance of RCCRO with a large number of optimization techniques on a large set of standard continuous benchmark functions. We find that RCCRO outperforms all the others on the average. We also propose an adaptive scheme for RCCRO which can improve the performance effectively. This shows that CRO is suitable for solving problems in the continuous domain.
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