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Multiple Elite Individual Guided Piecewise Search-Based Differential Evolution
Shubham Gupta; Shitu Singh; Rong Su; Shangce Gao; Jagdish Chand Bansal
Source PublicationIEEE/CAA Journal of Automatica Sinica
ISSN2329-9266
2023
Volume10Issue:1Pages:135-158
AbstractThe differential evolution (DE) algorithm relies mainly on mutation strategy and control parameters’ selection. To take full advantage of top elite individuals in terms of fitness and success rates, a new mutation operator is proposed. The control parameters such as scale factor and crossover rate are tuned based on their success rates recorded over past evolutionary stages. The proposed DE variant, MIDE, performs the evolution in a piecewise manner, i.e., after every predefined evolutionary stages, MIDE adjusts its settings to enrich its diversity skills. The performance of the MIDE is validated on two different sets of benchmarks: CEC 2014 and CEC 2017 (special sessions & competitions on real-parameter single objective optimization) using different performance measures. In the end, MIDE is also applied to solve constrained engineering problems. The efficiency and effectiveness of the MIDE are further confirmed by a set of experiments.
KeywordControl parameters differential Evolution metaheuristic algorithms mutation operator
DOI10.1109/JAS.2023.123018
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/50732
Collection学术期刊_IEEE/CAA Journal of Automatica Sinica
Recommended Citation
GB/T 7714
Shubham Gupta,Shitu Singh,Rong Su,et al. Multiple Elite Individual Guided Piecewise Search-Based Differential Evolution[J]. IEEE/CAA Journal of Automatica Sinica,2023,10(1):135-158.
APA Shubham Gupta,Shitu Singh,Rong Su,Shangce Gao,&Jagdish Chand Bansal.(2023).Multiple Elite Individual Guided Piecewise Search-Based Differential Evolution.IEEE/CAA Journal of Automatica Sinica,10(1),135-158.
MLA Shubham Gupta,et al."Multiple Elite Individual Guided Piecewise Search-Based Differential Evolution".IEEE/CAA Journal of Automatica Sinica 10.1(2023):135-158.
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