dc.creatorMelo L.P.
dc.creatorMiyazawa F.K.
dc.creatorPedrosa L.L.C.
dc.creatorSchouery R.C.S.
dc.date2016
dc.date2017-08-17T19:17:49Z
dc.date2017-08-17T19:17:49Z
dc.date.accessioned2018-03-29T05:27:28Z
dc.date.available2018-03-29T05:27:28Z
dc.identifierJournal Of Combinatorial Optimization. Springer New York Llc, p. 1 - 13, 2016.
dc.identifier1382-6905
dc.identifier10.1007/s10878-016-0064-2
dc.identifierhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84982131414&doi=10.1007%2fs10878-016-0064-2&partnerID=40&md5=eaf075f7b653777d2b9b357d491f069b
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/324180
dc.identifier2-s2.0-84982131414
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1358343
dc.descriptionIn the k-level facility location problem (FLP), we are given a set of facilities, each associated with one of k levels, and a set of clients. We have to connect each client to a chain of opened facilities spanning all levels, minimizing the sum of opening and connection costs. This paper considers the k-level stochastic FLP, with two stages, when the set of clients is only known in the second stage. There is a set of scenarios, each occurring with a given probability. A facility may be opened in any stage, however, the cost of opening a facility in the second stage depends on the realized scenario. The objective is to minimize the expected total cost. For the stage-constrained variant, when clients must be served by facilities opened in the same stage, we present a (Formula presented.)-approximation, improving on the 4-approximation by Wang et al. (Oper Res Lett 39(2):160–161, 2011) for each k. In the case with (Formula presented.), the algorithm achieves factors 2.56 and 2.78, resp., which improves the (Formula presented.)-approximation for (Formula presented.) by Wu et al. (Theor Comput Sci 562:213–226, 2015). For the non-stage-constrained version, we give the first approximation for the problem, achieving a factor of 3.495 for the case with (Formula presented.), and (Formula presented.) in general. © 2016 Springer Science+Business Media New York
dc.description1
dc.description13
dc.languageEnglish
dc.publisherSpringer New York LLC
dc.relationJournal of Combinatorial Optimization
dc.rightsfechado
dc.sourceScopus
dc.subjectApproximation Algorithm
dc.subjectMultilevel Facility Location Problem
dc.subjectStochastic Problem
dc.titleApproximation Algorithms For K-level Stochastic Facility Location Problems
dc.typeArtículos de revistas


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