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A framework for derivative free algorithm hybridization

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dc.contributor.author Angulo Sanchez-Herrera, Eusebio es_ES
dc.contributor.author Espinosa Aranda, Jose Luis es_ES
dc.contributor.author Garcia Rodenas, Ricardo es_ES
dc.date.accessioned 2013-05-09T06:10:29Z
dc.date.available 2013-05-09T06:10:29Z
dc.date.issued 2013 es_ES
dc.identifier.citation Adaptive and natural computing algorithms, 2013, 7824: 80-89 es_ES
dc.identifier.uri http://hdl.handle.net/10578/3007
dc.description.abstract Column generation is a basic tool for the solution of largescale mathematical programming problems. We present a class of column generation algorithms in which the columns are generated by derivative free algorithms, like population-based algorithms. This class can be viewed as a framework to define hybridization of free derivative algorithms. This framework has been illustrated in this article using the Simulated Annealing (SA) and Particle Swarm Optimization (PSO) algorithms, combining them with the Nelder-Mead (NM) method. Finally a set of computational experiments has been carried out to illustrate the potential of this framework. es_ES
dc.format text/plain en_US
dc.language.iso es en_US
dc.publisher Springer Berlin Heidelberg es_ES
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Ingenierías es_ES
dc.title A framework for derivative free algorithm hybridization es_ES
dc.type info:eu-repo/semantics/article en_US


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