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dc.contributor.authorGuo, Jingleien
dc.contributor.authorLi, Zhijianen
dc.contributor.authorYang, Shengxiangen
dc.date.accessioned2018-02-06T15:32:19Z
dc.date.available2018-02-06T15:32:19Z
dc.date.issued2018-01
dc.identifier.citationGuo, J., Li, Z. and Yang, S. (2018) Accelerating differential evolution based on a subset-to-subset survivor selection operator. Soft Computing, 23 (12), pp. 4113-4130en
dc.identifier.issn1432-7643
dc.identifier.issn1433-7479
dc.identifier.urihttp://hdl.handle.net/2086/15160
dc.descriptionThe file attached to this record is the author's final peer reviewed version.en
dc.description.abstractDifferential evolution (DE) is one of the most powerful and effective evolutionary algorithms for solving global optimization problems. However, just like all other metaheuristics, DE also has some drawbacks, such as slow and/or premature convergence. This paper proposes a new subset-to-subset selection operator to improve the convergence performance of DE by randomly dividing target and trial populations into several subsets and employing the ranking-based selection operator among corresponding subsets. The proposed framework gives more survival opportunities to trial vectors with better objective function values. Experimental results show that the proposed method significantly improves the performance of the original DE algorithm and several state-of-the-art DE variants on a series of benchmark functions.en
dc.language.isoen_USen
dc.publisherSpringeren
dc.subjectDifferential evolutionen
dc.subjectglobal optimizationen
dc.subjectsubset-to-subset survivor selectionen
dc.subjectconvergenceen
dc.titleAccelerating differential evolution based on a subset-to-subset survivor selection operatoren
dc.typeArticleen
dc.identifier.doihttps://doi.org/10.1007/s00500-018-3060-x
dc.researchgroupCentre for Computational Intelligenceen
dc.peerreviewedYesen
dc.funderEPSRC (Engineering and Physical Sciences Research Council)en
dc.projectidEP/K001310/1en
dc.cclicenceN/Aen
dc.date.acceptance2018-01-30en
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


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