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Investigation of Mutation Strategies in Differential Evolution for Solving Global Optimization Problems
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-3425-3837
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0001-9857-4317
2014 (English)In: ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING ICAISC 2014, PT I / [ed] Rutkowski, L Korytkowski, M Scherer, R Tadeusiewicz, R Zadeh, LA Zurada, JM, SPRINGER-VERLAG BERLIN , 2014, p. 372-383Conference paper, Published paper (Refereed)
Abstract [en]

Differential evolution (DE) is one competitive form of evolutionary algorithms. It heavily relies on mutating solutions using scaled differences of randomly selected individuals from the population to create new solutions. The choice of a proper mutation strategy is important for the success of an DE algorithm. This paper presents an empirical investigation to examine and compare the different mutation strategies for global optimization problems. Both solution quality and computational expense of DE variants were evaluated with experiments conducted on a set of benchmark problems. The results of such comparative study would offer valuable insight and information to develop optimal or adaptive mutation strategies for future DE researches and applications.

Place, publisher, year, edition, pages
SPRINGER-VERLAG BERLIN , 2014. p. 372-383
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 8467
Keyword [en]
Evolutionary Algorithm, Differential Evolution, Mutation Strategies, Global Optimization Problem
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-38393ISI: 000341246000032ISBN: 9783319071725 OAI: oai:DiVA.org:mdh-38393DiVA: diva2:1182140
Conference
13th International Conference on Artificial Intelligence and Soft Computing (ICAISC), JUN 01-05, 2014, Zakopane, POLAND
Available from: 2018-02-12 Created: 2018-02-12 Last updated: 2018-02-12Bibliographically approved

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Leon, MiguelXiong, Ning

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CiteExportLink to record
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  • ieee
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