Metaheuristic search based methods for unit commitment

dc.contributor.author Dewan Fayzur Rahman en
dc.contributor.author Ana Viana en
dc.contributor.author João Pedro Pedroso en
dc.date.accessioned 2017-11-20T10:41:11Z
dc.date.available 2017-11-20T10:41:11Z
dc.date.issued 2014 en
dc.description.abstract This paper presents two new solution approaches capable of finding optimal solutions for the thermal unit commitment problem in power generation planning. The approaches explore the concept of "matheuristics", a term usually used to refer to an optimization algorithm that hybridizes (meta)heuristics with mixed integer programming solvers, in order to speed up convergence to optimality for large scale instances. Two algorithms are proposed: "local branching", and an hybridization of particle swarm optimization with a mixed integer programming solver. From extensive computational tests on a broad set of benchmarks, the algorithms were found to be able to solve large instances. Optimal solutions were obtained for several well-known situations with dramatic reductions in CPU time for the larger cases, when compared to previously proposed exact methods. en
dc.identifier.uri http://repositorio.inesctec.pt/handle/123456789/3563
dc.identifier.uri http://dx.doi.org/10.1016/j.ijepes.2014.01.038 en
dc.language eng en
dc.relation 3708 en
dc.relation 5425 en
dc.relation 4747 en
dc.rights info:eu-repo/semantics/embargoedAccess en
dc.title Metaheuristic search based methods for unit commitment en
dc.type article en
dc.type Publication en
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