Differential Evolution: A survey of theoretical analyses

被引：317

作者：

Opara, Karol R. ^{[1
]}

Arabas, Jaroslaw ^{[2
]}

机构：

[1] Polish Acad Sci, Syst Res Inst, Warsaw, Poland

[2] Warsaw Univ Technol, Inst Comp Sci, Warsaw, Poland

来源：

SWARM AND EVOLUTIONARY COMPUTATION | 2019年 / 44卷

关键词：

DE population dynamics; Diversity; Convergence; Global optimization; Evolutionary algorithm; CONVERGENCE ANALYSIS; POPULATION-DYNAMICS; DRIFT ANALYSIS; NO FREE; ALGORITHMS; OPTIMIZATION; CROSSOVER; SELECTION; SPACE; SIZE;

D O I：

10.1016/j.swevo.2018.06.010

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Differential Evolution (DE) is a state-of-the art global optimization technique. Considerable research effort has been made to improve this algorithm and apply it to a variety of practical problems. Nevertheless, analytical studies concerning DE are rather rare. This paper surveys the theoretical results obtained so far for DE. A discussion of genetic operators characteristic of DE is coupled with an overview of the population diversity and dynamics models. A comprehensive view on the current-day understanding of the underlying mechanisms of DE is complemented by a list of promising research directions.

引用

页码：546 / 558

页数：13

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