期刊
INFORMATION SCIENCES
卷 178, 期 23, 页码 4421-4433出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2008.07.031
关键词
Steady-state genetic algorithms; Useful diversity; Replacement strategy
In this paper, we propose a replacement strategy for steady-state genetic algorithms that considers two features of the candidate chromosome to be included into the population: a measure of the contribution of diversity to the population and the fitness function. In particular, the proposal tries to replace an individual in the population with worse values for these two features. In this way, the diversity of the population becomes increased and the quality of the solutions gets better, thus preserving high levels of useful diversity. Experimental results show the proposed replacement strategy achieved significant performance for problems with different difficulties, with regards to other replacement strategies presented in the literature. (C) 2008 Elsevier Inc. All rights reserved.
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