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dc.contributor.authorWeber, Matthieuen
dc.contributor.authorTirronen, Villeen
dc.contributor.authorNeri, Ferranteen
dc.identifier.citationWeber, M., Tirronen, V. and Neri, F. (2010) Scale Factor Inheritance Mechanism in Distributed Differential Evolution. Soft Computing - A Fusion of Foundations, Methodologies and Applications, 14, (11), pages 1187-1207en
dc.description.abstractThis article proposes a distributed differential evolution which employs a novel self-adaptive scheme, namely scale factor inheritance. In the proposed algorithm, the population is distributed over several sub-populations allocated according to a ring topology. Each sub-population is characterized by its own scale factor value. With a probabilistic criterion, that individual displaying the best performance is migrated to the neighbor population and replaces a pseudo-randomly selected individual of the target sub-population. The target sub-population inherits not only this individual but also the scale factor if it seems promising at the current stage of evolution. In addition, a perturbation mechanism enhances the exploration feature of the algorithm. The proposed algorithm has been run on a set of various test problems and then compared to two sequential differential evolution algorithms and three distributed differential evolution algorithms recently proposed in literature and representing state-of-the-art in the field. Numerical results show that the proposed approach seems very efficient for most of the analyzed problems, and outperforms all other algorithms considered in this study.en
dc.subjectdifferential evolutionen
dc.subjectdistributed evolutionary algorithmsen
dc.subjectevolutionary algorithmsen
dc.subjectcontinuous optimizationen
dc.titleScale Factor Inheritance Mechanism in Distributed Differential Evolutionen
dc.researchgroupCentre for Computational Intelligenceen
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en

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