An adaptive differential evolution algorithm based on belief space and generalized opposition-based learning for resource allocation

Differential evolution (DE) algorithm is prone to premature convergence and local optimization in solving complex optimization problems. In order to solve these problems, the belief space strategy, generalized opposition-based learning strategy and parameter adaptive strategy are introduced into DE...

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Vydané v:	Applied soft computing Ročník 127; s. 109419
Hlavní autori:	Deng, Wu, Ni, Hongcheng, Liu, Yi, Chen, Huiling, Zhao, Huimin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.09.2022
Predmet:	Belief space Differential evolution Gate allocation Global optimization Opposition-based learning Parameter adaptation Differential evolution Global optimization Gate allocation Parameter adaptation Belief space Opposition-based learning
ISSN:	1568-4946, 1872-9681
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