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A 2-level metaheuristic for the set covering problem

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Autor dc.contributor.author Valenzuela C.
Autor dc.contributor.author Crawford B.
Autor dc.contributor.author Soto R.
Autor dc.contributor.author Monfroy E.
Autor dc.contributor.author Paredes F.
Fecha Ingreso dc.date.accessioned 2014-04-05T00:14:33Z
Fecha Disponible dc.date.available 2014-04-05T00:14:33Z
Fecha en Repositorio dc.date.issued 2014-04-04
dc.description.abstract Metaheuristics are solution methods which combine local improvement procedures and higher level strategies for solving combinatorial and nonlinear optimization problems. In general, metaheuristics require an important amount of effort focused on parameter setting to improve its performance. In this work a 2-level metaheuristic approach is proposed so that Scatter Search and Ant Colony Optimization act as "low level" metaheuristics, whose parameters are set by a "higher level" Genetic Algorithm during execution, seeking to improve the performance and to reduce the maintenance. The Set Covering Problem is taken as reference since is one of the most important optimization problems, serving as basis for facility location problems, airline crew scheduling, nurse scheduling, and resource allocation. © 2006-2012 by CCC Publications. en_US
dc.source International Journal of Computers, Communications and Control
Link Descarga dc.source.uri http://www.scopus.com/inward/record.url?eid=2-s2.0-84862661432&partnerID=40&md5=71d3527d7e50fcbb2524e1ddac197829
Title dc.title A 2-level metaheuristic for the set covering problem en_US
Tipo dc.type Article


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