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Solving the set covering problem with binary cat swarm optimization

dc.contributor.authorCrawford, B.
dc.contributor.authorSoto, R.
dc.contributor.authorBerrÍos, N.
dc.contributor.authorJohnson, F.
dc.contributor.authorParedes, F.
dc.date.accessioned2025-10-31T18:32:24Z
dc.date.available2025-10-31T18:32:24Z
dc.date.issued2015
dc.identifier.urihttps://hdl.handle.net/20.500.12805/4629
dc.description.abstractThe Set Covering Problem is a formal model for many practical optimization problems. It consists in finding a subset of columns in a zero–one matrix such that they cover all the rows of the matrix at a minimum cost. To solve the Set Covering Problem we use a metaheuristic called Binary Cat Swarm Optimization. This metaheuristic is a binary version of Cat Swarm Optimization generated by observing cat behavior. Cats have two modes of behavior: seeking mode and tracing mode. We are the first ones to use this metaheuristic to solve the Set Covering Problem, for this the proposed algorithm has been tested on 65 benchmarks instances.en_US
dc.formatapplication/pdf
dc.language.isoeng
dc.publisherSpringer Verlag
dc.relation.ispartofurn:issn:0302-9743
dc.rightshttps://purl.org/coar/access_right/c_abf2
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0/
dc.subjectOptimized Logistics and Vehicle Routing Solutionsen_US
dc.subjectInnovative Algorithms for Set Covering Optimizationen_US
dc.titleSolving the set covering problem with binary cat swarm optimizationen_US
dc.typehttps://purl.org/coar/resource_type/c_5794
dc.identifier.doihttps://doi.org/10.1007/978-3-319-20466-6_4
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#2.00.00
dc.type.otherConference Paper
dc.identifier.journalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.type.versionhttps://purl.org/coar/version/c_970fb48d4fbd8a85


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