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dc.contributor.authorCrawford B.
dc.contributor.authorSoto R.
dc.contributor.authorCaballero H.
dc.contributor.authorOlguín E.
dc.date.accessioned2020-09-02T22:15:36Z
dc.date.available2020-09-02T22:15:36Z
dc.date.issued2016
dc.identifier10.1007/978-3-319-33625-1_44
dc.identifier.citation464, , 491-500
dc.identifier.issn21945357
dc.identifier.urihttps://hdl.handle.net/20.500.12728/4123
dc.descriptionIn this paper, we study a classical problem in combinatorics and computer science, Set Covering Problem. It is one of Karp’s 21 NP-complete problems, using a new and original metaheuristic, Cat Swarm Optimization. This algorithm imitates the domestic cat through two states: seeking and tracing mode. The OR-Library of Beasley instances were used for the benchmark with additional fitness function, thus the problem was transformed from Mono-objective to Bi-objective. The Cat Swarm Optimization finds a set solution non-dominated based on Pareto concepts, and an external file for storing them. The results are promising for further continue in future work optimizing this problem. © Springer International Publishing Switzerland 2016.
dc.language.isoen
dc.publisherSpringer Verlag
dc.sourceSilhavy R.Senkerik R.Oplatkova Z.K.Silhavy P.Prokopova Z.
dc.subjectCat swarm optimization
dc.subjectEvolutionary algorithm
dc.subjectMultiobjective cat swarm optimization
dc.subjectMultiobjective problems
dc.subjectPareto dominance
dc.subjectSwarm optimization
dc.subjectAlgorithms
dc.subjectArtificial intelligence
dc.subjectComputational complexity
dc.subjectEvolutionary algorithms
dc.subjectIntelligent systems
dc.subjectMultiobjective optimization
dc.subjectClassical problems
dc.subjectExternal files
dc.subjectFitness functions
dc.subjectMulti-objective problem
dc.subjectPareto dominance
dc.subjectSet covering problem
dc.subjectSwarm optimization
dc.subjectSwarm optimization algorithms
dc.subjectOptimization
dc.titleA bi-objetive Cat Swarm Optimization algorithm for set covering problem
dc.typeConference Paper


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