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dc.contributor.authorApolloni, Javier
dc.contributor.authorGarcía-Nieto, José
dc.contributor.authorAlba, Enrique
dc.contributor.authorLeguizamón, Guillermo
dc.date.accessioned2018-01-26T06:28:14Z
dc.date.available2018-01-26T06:28:14Z
dc.date.issued2014
dc.identifier.citationApplied Mathematics and Computation. 2014, vol. 236, p. 351-366.cs
dc.identifier.issn0096-3003
dc.identifier.issn1873-5649
dc.identifier.urihttp://hdl.handle.net/10084/123436
dc.description.abstractThis paper presents a new distributed Differential Evolution (dDE) algorithm and provides an exhaustive evaluation of it by using two standard benchmarks. One of them was proposed in the special session of Real-Parameter Optimization of CEC' 05, and the other was proposed in the special session of Large Scale Global Optimization of CEC 08. We statistically validate and compare our results versus all other techniques presented in these special sessions. This means that more than 25 problems, with different dimensions: 30, 50, 100, and 500 variables, are evaluated; and 15 algorithms are compared in the experiments. Our dDE is simple, accurate, and competitive when applied to a wide variety of problems, with scaling dimensions, and different function features: noisy, non-separable, multimodal, rotated, etc.cs
dc.language.isoencs
dc.publisherElseviercs
dc.relation.ispartofseriesApplied Mathematics and Computationcs
dc.relation.urihttps://doi.org/10.1016/j.amc.2014.03.083cs
dc.rightsCopyright © 2014 Elsevier Inc. All rights reserved.cs
dc.subjectdistributed Differential Evolutioncs
dc.subjectnon-parametric testscs
dc.subjectbenchmarkingcs
dc.titleEmpirical evaluation of distributed Differential Evolution on standard benchmarkscs
dc.typearticlecs
dc.identifier.doi10.1016/j.amc.2014.03.083
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume236cs
dc.description.lastpage366cs
dc.description.firstpage351cs
dc.identifier.wos000335899200034


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