A heuristic algorithm based on multi-assignment procedures for nurse scheduling

dc.contributorUniversidade Estadual Paulista (UNESP)
dc.creatorConstantino, Ademir Aparecido
dc.creatorLanda-Silva, Dario
dc.creatorMelo, Everton Luiz de
dc.creatorMendonça, Candido Ferreira Xavier de
dc.creatorRizzato, Douglas Baroni
dc.creatorRomão, Wesley
dc.date2014-05-27T11:28:50Z
dc.date2016-10-25T18:46:45Z
dc.date2014-05-27T11:28:50Z
dc.date2016-10-25T18:46:45Z
dc.date2013-04-03
dc.date.accessioned2017-04-06T02:19:35Z
dc.date.available2017-04-06T02:19:35Z
dc.identifierAnnals of Operations Research, p. 1-19.
dc.identifier0254-5330
dc.identifier1572-9338
dc.identifierhttp://hdl.handle.net/11449/75055
dc.identifierhttp://acervodigital.unesp.br/handle/11449/75055
dc.identifier10.1007/s10479-013-1357-9
dc.identifierWOS:000339330000011
dc.identifier2-s2.0-84904167882
dc.identifierhttp://dx.doi.org/10.1007/s10479-013-1357-9
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/895806
dc.descriptionThis paper tackles a Nurse Scheduling Problem which consists of generating work schedules for a set of nurses while considering their shift preferences and other requirements. The objective is to maximize the satisfaction of nurses' preferences and minimize the violation of soft constraints. This paper presents a new deterministic heuristic algorithm, called MAPA (multi-assignment problem-based algorithm), which is based on successive resolutions of the assignment problem. The algorithm has two phases: a constructive phase and an improvement phase. The constructive phase builds a full schedule by solving successive assignment problems, one for each day in the planning period. The improvement phase uses a couple of procedures that re-solve assignment problems to produce a better schedule. Given the deterministic nature of this algorithm, the same schedule is obtained each time that the algorithm is applied to the same problem instance. The performance of MAPA is benchmarked against published results for almost 250,000 instances from the NSPLib dataset. In most cases, particularly on large instances of the problem, the results produced by MAPA are better when compared to best-known solutions from the literature. The experiments reported here also show that the MAPA algorithm finds more feasible solutions compared with other algorithms in the literature, which suggest that this proposed approach is effective and robust. © 2013 Springer Science+Business Media New York.
dc.languageeng
dc.relationAnnals of Operations Research
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectAssignment problem
dc.subjectCombinatorial optimization
dc.subjectHeuristic algorithms
dc.subjectNurse scheduling problem
dc.titleA heuristic algorithm based on multi-assignment procedures for nurse scheduling
dc.typeOtro


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