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dc.contributor.authorSoto R.
dc.contributor.authorCrawford B.
dc.contributor.authorFernandez N.
dc.contributor.authorReyes V.
dc.contributor.authorNiklander S.
dc.contributor.authorAraya I.
dc.date.accessioned2020-09-02T22:28:39Z
dc.date.available2020-09-02T22:28:39Z
dc.date.issued2017
dc.identifier10.1007/978-3-319-62434-1_32
dc.identifier.citation10061 LNAI, , 391-398
dc.identifier.issn03029743
dc.identifier.urihttps://hdl.handle.net/20.500.12728/6294
dc.descriptionIn this paper we solve the Manufacturing Cell Design Problem. This problem considers the grouping of different machines into sets or cells with the objective of minimizing the movement of material. To solve this problem we use the Black Hole algorithm, a modern population-based metaheuristic that is inspired by the phenomenon of the same name. At each iteration of the search, the best candidate solution is selected to be the black hole and other candidate solutions, known as stars, are attracted by the black hole. If one of these stars get too close to the black hole it disappears, generating a new random star (solution). Our approach has been tested by using a well-known set of benchmark instances, reaching optimal values in all of them. © Springer International Publishing AG 2017.
dc.language.isoen
dc.publisherSpringer Verlag
dc.sourceHerrera-Alcantara O.Sidorov G.
dc.subjectBlack Hole algorithm
dc.subjectManufacturing cell design problems
dc.subjectMetaheuristics
dc.subjectArtificial intelligence
dc.subjectBenchmarking
dc.subjectCells
dc.subjectCytology
dc.subjectFlexible manufacturing systems
dc.subjectGravitation
dc.subjectIterative methods
dc.subjectManufacture
dc.subjectSoft computing
dc.subjectStars
dc.subjectBlack holes
dc.subjectCell design
dc.subjectMeta heuristics
dc.subjectMetaheuristic
dc.subjectOptimal values
dc.subjectProblem solving
dc.titleSolving manufacturing cell design problems using the black hole algorithm
dc.typeConference Paper


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