Show simple item record

dc.contributor.authorCrawford B.
dc.contributor.authorSoto R.
dc.contributor.authorRiquelme L.
dc.contributor.authorOlguín E.
dc.date.accessioned2020-09-02T22:16:04Z
dc.date.available2020-09-02T22:16:04Z
dc.date.issued2016
dc.identifier10.1007/978-3-319-33625-1_25
dc.identifier.citation464, , 273-283
dc.identifier.issn21945357
dc.identifier.urihttps://hdl.handle.net/20.500.12728/4182
dc.descriptionBiogeography-Based Optimization Algorithm (BBOA) is a kind of new global optimization algorithm inspired by biogeography. It mimics the migration behavior of animals in nature to solve optimization and engineering problems. In this paper, BBOA for the Set Covering Problem (SCP) is proposed. SCP is a classic combinatorial problem from NP-hard list problems. It consist to find a set of solutions that cover a range of needs at the lowest possible cost following certain constraints. In addition, we provide a new feature for improve performance of BBOA, improving stagnation in local optimum. With this, the experiment results show that BBOA is very good at solving such problems. © Springer International Publishing Switzerland 2016.
dc.language.isoen
dc.publisherSpringer Verlag
dc.sourceSilhavy R.Senkerik R.Oplatkova Z.K.Silhavy P.Prokopova Z.
dc.subjectBiogeography-Based Optimization Algorithm
dc.subjectSet Covering Problem
dc.subjectAlgorithms
dc.subjectArtificial intelligence
dc.subjectEcology
dc.subjectGlobal optimization
dc.subjectHeuristic algorithms
dc.subjectIntelligent systems
dc.subjectProblem solving
dc.subjectBiogeography-based optimization algorithms
dc.subjectCombinatorial problem
dc.subjectEngineering problems
dc.subjectGlobal optimization algorithm
dc.subjectImprove performance
dc.subjectLocal optima
dc.subjectNP-hard
dc.subjectSet covering problem
dc.subjectOptimization
dc.titleBiogeography-Based Optimization Algorithm for solving the set covering problem
dc.typeConference Paper


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record