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Free Search Differential Evolution

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2 Author(s)
Mahamed G. H. Omran ; Department of Computer Science, Gulf, University for Science and Technology, Kuwait ; Andries P. Engelbrecht

Free search differential evolution (FSDE) is a new, population-based meta-heuristic algorithm that is a hybrid of concepts from free search (FS), differential evolution (DE) and opposition-based learning. The performance of the proposed approach is investigated and compared with DE and one of the recent variants of DE when applied to ten benchmark functions. The experiments conducted show that FSDE provides excellent results with the added advantage of no parameter tuning.

Published in:

2009 IEEE Congress on Evolutionary Computation

Date of Conference:

18-21 May 2009