Modified Nelder-Mead self organizing migrating algorithm for function optimization and its application

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• 作者：Seema Agrawal^a ; ^{seemagrwl7@gmail.com} ; Dipti Singh^b
• 关键词：Self organizing migrating algorithm ; Nelder Mead crossover operator ; Genetic algorithm ; Particle swarm optimization ; Function optimization ; Hybridization
• 刊名：Applied Soft Computing
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：51
• 期：Complete
• 页码：341-350
• 全文大小：698 K
• 卷排序：51

文摘

This paper presents a modified Nelder-Mead self organizing migrating algorithm for function optimization and its application named mNM-SOMA. In the proposed algorithm SOMA is hybridized with modified Nelder Mead crossover operator. To validate the efficiency of the proposed algorithm, it is tested on 15 benchmark test problems and one real life application taken from the literature. The obtained results are compared with the results of other state of the art algorithms.