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Using the Bee Colony Optimization Method to Solve the Weighted Set Covering Problem

dc.contributor.authorCrawford B.
dc.contributor.authorSoto R.
dc.contributor.authorCuesta R.
dc.contributor.authorParedes F.
dc.date.accessioned2020-09-02T22:15:37Z
dc.date.available2020-09-02T22:15:37Z
dc.date.issued2014
dc.identifier10.1007/978-3-319-07857-1_86
dc.identifier.citation434 PART I, , 493-497
dc.identifier.issn18650929
dc.identifier.urihttps://hdl.handle.net/20.500.12728/4131
dc.descriptionThe Weighted Set Covering Problem is a formal model for many practical optimization problems. In this problem the goal is to choose a subset of columns of minimal cost covering every row. Here, we present a novel application of the Artificial Bee Colony algorithm to solve the Weighted Set Covering Problem. The Artificial Bee Colony algorithm is a recent Swarm Metaheuristic technique based on the intelligent foraging behavior of honey bees. Experimental results show that our Artificial Bee Colony algorithm is competitive in terms of solution quality with other recent metaheuristic approaches. © Springer International Publishing Switzerland 2014.
dc.language.isoen
dc.publisherSpringer Verlag
dc.subjectArtificial Bee Colony Algorithm
dc.subjectSwarm Intelligence
dc.subjectWeighted Set Covering Problem
dc.subjectArtificial intelligence
dc.subjectOptimization
dc.subjectArtificial bee colony algorithms
dc.subjectBee colony optimizations
dc.subjectMeta-heuristic approach
dc.subjectMeta-heuristic techniques
dc.subjectNovel applications
dc.subjectOptimization problems
dc.subjectSwarm Intelligence
dc.subjectWeighted set covering problems
dc.subjectAlgorithms
dc.titleUsing the Bee Colony Optimization Method to Solve the Weighted Set Covering Problem
dc.typeConference Paper


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