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Investigation of mutation strategies in differential evolution for solving global optimization problems
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0002-3425-3837
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0001-9857-4317
2014 (engelsk)Inngår i: Artificial Intelligence and Soft Computing: 13th International Conference, ICAISC 2014, Zakopane, Poland, June 1-5, 2014, Proceedings, Part I, Springer, 2014, nr PART 1, s. 372-383Kapittel i bok, del av antologi (Fagfellevurdert)
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. 

sted, utgiver, år, opplag, sider
Springer, 2014. nr PART 1, s. 372-383
Emneord [en]
Differential Evolution, Evolutionary Algorithm, Global Optimization Problem, Mutation Strategies
HSV kategori
Identifikatorer
URN: urn:nbn:se:mdh:diva-25594DOI: 10.1007/978-3-319-07173-2_32Scopus ID: 2-s2.0-84902590522ISBN: 9783319071725 (tryckt)OAI: oai:DiVA.org:mdh-25594DiVA, id: diva2:732637
Konferanse
1 June 2014 through 5 June 2014, Zakopane
Tilgjengelig fra: 2014-07-04 Laget: 2014-07-04 Sist oppdatert: 2016-10-26bibliografisk kontrollert

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