期刊
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
卷 15, 期 1, 页码 55-66出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TEVC.2010.2087271
关键词
Control parameters; differential evolution; global numerical optimization; trial vector generation strategy
资金
- National Natural Science Foundation of China [60805027, 90820302]
- Research Fund for the Doctoral Program of Higher Education of China [200805330005]
- Graduate Innovation Fund of Hunan Province of China [CX2009B039]
Trial vector generation strategies and control parameters have a significant influence on the performance of differential evolution (DE). This paper studies whether the performance of DE can be improved by combining several effective trial vector generation strategies with some suitable control parameter settings. A novel method, called composite DE (CoDE), has been proposed in this paper. This method uses three trial vector generation strategies and three control parameter settings. It randomly combines them to generate trial vectors. CoDE has been tested on all the CEC2005 contest test instances. Experimental results show that CoDE is very competitive.
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