A New Fruit Fly Optimization Algorithm Based on Differential Evolution

Zhang Dabin (), Ye Jia, Zhou Zhigang and Luan Yuqi
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Zhang Dabin: College of Mathematics and Information, South China Agricultural University, Guangzhou510642, China
Ye Jia: School of Information Management, Central China Normal University, WuHan430079, China
Zhou Zhigang: School of Information Management, Central China Normal University, WuHan430079, China
Luan Yuqi: School of Information Management, Central China Normal University, WuHan430079, China

Journal of Systems Science and Information, 2015, vol. 3, issue 4, 365-373

Abstract: In order to overcome the problem of low convergence precision and easily relapsing into local extremum in fruit fly optimization algorithm (FOA), this paper adds the idea of differential evolution to fruit fly optimization algorithm so as to optimizing and a algorithm of fruit fly optimization based on differential evolution is proposed (FOADE). Adding the operating of mutation, crossover and selection of differential evolution to FOA after each iteration, which can jump out local extremum and continue to optimize. Compared to FOA, the experimental results show that FOADE has the advantages of better global searching ability, faster convergence and more precise convergence.

Keywords: fruit fly optimization algorithm; differential evolution; optimization; global optimization (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:jossai:v:3:y:2015:i:4:p:365-373:n:7

DOI: 10.1515/JSSI-2015-0365

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