Set covering problem resolution by Biogeography-Based Optimization Algorithm

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dc.contributor.authorCrawford, B.es_ES
dc.contributor.authorSoto, R.es_ES
dc.contributor.authorRiquelme, L.es_ES
dc.contributor.authorOlguín, E.es_ES
dc.contributor.authorMisra, S.es_ES
dc.date.accessioned6/22/2022 13:33
dc.date.accessioned2022-09-30T16:09:26Z
dc.date.available6/22/2022 13:33
dc.date.available2022-09-30T16:09:26Z
dc.date.issued2016
dc.description.abstractThe research on Artificial Intelligence and Operational Research has provided models and techniques to solve many industrial problems. For instance, many real life problems can be formulated as a Set Covering Problem (SCP). The SCP is a classic NP-hard combinatorial problem consisting in find a set of solutions that cover a range of needs at the lowest possible cost following certain constraints. In this work, we use a recent metaheuristic called Biogeography-Based Optimization Algorithm (BBOA) inspired by biogeography, which mimics the migration behavior of animals in nature to solve optimization and engineering problems. In this paper, BBOA for the SCP is proposed. In addition, to improve performance we provide a new feature for the BBOA, which improve stagnation in local optimum. Finally, the experiment results show that BBOA is a excellent method for solving such problems. © Springer International Publishing Switzerland 2016.es_ES
dc.formatapplication/pdfes_ES
dc.identifier.doi10.1007/978-3-319-42085-1_12es_ES
dc.identifier.urihttps://doi.org/10.1007/978-3-319-42085-1_12
dc.language.isoenges_ES
dc.publisherSpringer Verlages_ES
dc.rightsinfo:eu-repo/semantics/closedAccesses_ES
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/es_ES
dc.sourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)es_ES
dc.subjectComputer Sciencees_ES
dc.subjectMathematicses_ES
dc.subject.ocdehttp://purl.org/pe-repo/ocde/ford#1.02.01es_ES
dc.titleSet covering problem resolution by Biogeography-Based Optimization Algorithmes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_ES
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