Title :
Free Search Differential Evolution
Author :
Omran, Mahamed G H ; Engelbrecht, Andries P.
Author_Institution :
Dept. of Comput. Sci., Gulf Univ. for Sci. & Technol., Mishref
Abstract :
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.
Keywords :
learning (artificial intelligence); optimisation; search problems; stochastic processes; free search differential evolution; opposition-based learning; population-based metaheuristic algorithm; Africa; Animals; Computer science; Design engineering; Design optimization; Image processing; Optimization methods; Pattern recognition; Space technology; Stochastic resonance;
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
DOI :
10.1109/CEC.2009.4982937
