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dc.contributor.authorSoto R.
dc.contributor.authorCrawford B.
dc.contributor.authorGalleguillos C.
dc.contributor.authorBarraza J.
dc.contributor.authorLizama S.
dc.contributor.authorMuñoz A.
dc.contributor.authorVilches J.
dc.contributor.authorMisra S.
dc.contributor.authorParedes F.
dc.date.accessioned2020-09-02T22:28:40Z
dc.date.available2020-09-02T22:28:40Z
dc.date.issued2015
dc.identifier10.1007/978-3-319-21404-7_14
dc.identifier.citation9155, , 187-202
dc.identifier.issn03029743
dc.identifier.urihttps://hdl.handle.net/20.500.12728/6298
dc.descriptionThe set covering problem is a classical model in the subject of combinatorial optimization for service allocation, that consists in finding a set of solutions for covering a range of needs at the lowest possible cost. In this paper, we report various approximate methods to solve this problem, such as Cuckoo Search, Bee Colony, Firefly Optimization, and Electromagnetism-Like Algorithms. We illustrate experimental results of these metaheuristics for solving a set of 65 non-unicost set covering problems from the Beasley’s OR-Library. © Springer International Publishing Switzerland 2015.
dc.language.isoen
dc.publisherSpringer Verlag
dc.sourceMisra S.Apduhan B.O.Murgante B.Gavrilova M.L.Taniar D.Gervasi O.Misra S.Torre C.Rocha A.M.A.C.
dc.subjectBee colony algorithm
dc.subjectCombinatorial optimization
dc.subjectCuckoo search algorithm
dc.subjectElectromagnetism-Like algorithm
dc.subjectFirefly optimization algorithm
dc.subjectSet covering problem
dc.subjectAlgorithms
dc.subjectBioluminescence
dc.subjectCombinatorial optimization
dc.subjectFactory automation
dc.subjectProblem solving
dc.subjectBee colony algorithms
dc.subjectCuckoo search algorithms
dc.subjectElectromagnetism-like algorithm
dc.subjectOptimization algorithms
dc.subjectSet covering problem
dc.subjectOptimization
dc.titleComparing cuckoo search, bee colony, firefly optimization, and electromagnetism-like algorithms for solving the set covering problem
dc.typeConference Paper


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