Differential Evolution: A survey of theoretical analyses

Karol Opara , Jarosław Arabas

Abstract

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.
Author Karol Opara (SRI)
Karol Opara,,
- Systems Research Institute
, Jarosław Arabas (FEIT / IN)
Jarosław Arabas,,
- The Institute of Computer Science
Journal seriesSwarm and Evolutionary Computation, ISSN 2210-6502, (A 50 pkt)
Issue year2019
Vol44
Pages546-558
Publication size in sheets0.6
Keywords in EnglishDE population dynamics; Diversity; Convergence; Global optimization; Evolutionary algorithm
ASJC Classification2600 General Mathematics; 1700 General Computer Science
DOIDOI:10.1016/j.swevo.2018.06.010
URL https://www.sciencedirect.com/science/article/pii/S2210650217304224
projectDevelopment of new algorithms in the areas of software and computer architecture, artificial intelligence and information systems and computer graphics . Project leader: Arabas Jarosław, , Phone: +48 22 234 7432, start date 01-08-2018, planned end date 30-09-2019, II/2018/DS/1, Implemented
WEiTI Działalność statutowa
Languageen angielski
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Opara_Arabas_differential_evolution_2019.pdf 623.4 KB
Score (nominal)50
ScoreMinisterial score = 50.0, 30-04-2019, ArticleFromJournal
Ministerial score (2013-2016) = 50.0, 22-04-2019, ArticleFromJournal
Publication indicators WoS Citations = 3; Scopus SNIP (Source Normalised Impact per Paper): 2016 = 2.756; WoS Impact Factor: 2017 = 3.818 (2) - 2017=4.607 (5)
Citation count*16 (2019-08-15)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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