Super-fit control adaptation in memetic differential evolution frameworks
作者： Andrea Caponio , Ferrante Neri , Ville Tirronen
DOI: 10.1007/S00500-008-0357-1
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摘要: This paper proposes the super-fit memetic differential evolution (SFMDE). This algorithm employs a differential evolution (DE) framework hybridized with three meta-heuristics, each having different roles and features. Particle Swarm Optimization assists the DE in the beginning of the optimization process by helping to generate a super-fit individual. The two other meta-heuristics are local searchers adaptively coordinated by means of an index measuring quality of the super-fit individual with respect to the rest of the population. The …
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