Solving biobjective set covering problem using binary cat swarm optimization algorithm

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dc.contributor.authorCrawford, B.es_ES
dc.contributor.authorSoto, R.es_ES
dc.contributor.authorCaballero, H.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 set cover problem is a classical question in combinatorics, computer science and complexity theory. It is one of Karp’s 21 NP-complete problems shown to be NP-complete in 1972. Several algorithms have been proposed to solve this problem, based on genetic algorithms (GA), Particle Swarm Optimizer (PSO) and in recent years algorithms based in behavior algorithms based groups or herds of animals, such as frogs, bats, bees and domestic cats. This work presents the basic features of the algorithm based on the behavior of domestic cats and results to solve the SCP bi-objective, experimental results and opportunities to improve results using adaptive techniques applied to Cat Swarm Optimization. For this purpose we will use instances of SCP OR-Library of Beasley by adding an extra function fitness to transform the Beasly instance to Bi-Objective problem. © Springer International Publishing Switzerland 2016.es_ES
dc.formatapplication/pdfes_ES
dc.identifier.doi10.1007/978-3-319-42085-1_17es_ES
dc.identifier.urihttps://doi.org/10.1007/978-3-319-42085-1_17
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.titleSolving biobjective set covering problem using binary cat swarm optimization algorithmes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_ES
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