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dc.contributor.authorBergmeir, Christoph Norbertes_ES
dc.contributor.authorMolina Cabrera, Danieles_ES
dc.contributor.authorBenítez Sánchez, José Manuel es_ES
dc.identifier.citationBergmeir, C.N.; Molina, D.; Benítez Sánchez, J.M. Memetic Algorithms with Local Search Chains in R: The Rmalschains Package. Journal of Statistical Software, 75(4): 1-33 (2016). []es_ES
dc.description.abstractGlobal optimization is an important field of research both in mathematics and computer sciences. It has applications in nearly all fields of modern science and engineering. Memetic algorithms are powerful problem solvers in the domain of continuous optimization, as they offer a trade-off between exploration of the search space using an evolutionary algorithm scheme, and focused exploitation of promising regions with a local search algorithm. In particular, we describe the memetic algorithms with local search chains (MA-LS-Chains) paradigm, and the R package Rmalschains, which implements them. MA-LS-Chains has proven to be effective compared to other algorithms, especially in high-dimensional problem solving. In an experimental study, we demonstrate the advantages of using Rmalschains for high-dimension optimization problems in comparison to other optimization methods already available in R.en_EN
dc.description.sponsorshipThis work was supported in part by the Spanish Ministry of Science and Innovation (MICINN) under Project TIN-2009-14575. The work was performed while C. Bergmeir held a scholarship from the Spanish Ministry of Education (MEC) of the “Programa de Formación del Profesorado Universitario (FPU)”.en_EN
dc.publisherAmerican Statistical Associationes_ES
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs 3.0 License
dc.subjectContinuous optimizationen_EN
dc.subjectMemetic algorithmsen_EN
dc.subjectR (Software)en_EN
dc.titleMemetic Algorithms with Local Search Chains in R: The Rmalschains Packageen_EN

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