Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/446
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dc.contributor.authorMarić, Miroslaven_US
dc.contributor.authorStanimirović, Zoricaen_US
dc.contributor.authorBožović, Srdjanen_US
dc.date.accessioned2022-08-13T09:27:51Z-
dc.date.available2022-08-13T09:27:51Z-
dc.date.issued2015-04-01-
dc.identifier.issn02545330en
dc.identifier.urihttps://research.matf.bg.ac.rs/handle/123456789/446-
dc.description.abstractLong-term health care facilities have gained an important role in today’s health care environments, due to the global trend of aging of human population. This paper considers the problem of network design in health-care systems, named the Long-Term Care Facility Location Problem (LTCFLP), which deals with determining locations for long-term care facilities among given potential sites. The objective is to minimize the maximal number of patients assigned to established facilities. We have developed an efficient hybrid method, based on combining the Evolutionary Approach (EA) with modified Variable Neighborhood Search method (VNS). The EA method is used in order to obtain a better initial solution that will enable the VNS to solve the LTCFLP more efficiently. The proposed hybrid algorithm is additionally enhanced by an exchange local search procedure. The algorithm is benchmarked on a data set from the literature with up to 80 potential candidate sites and on large-scale instances with up to 400 nodes. Presented computational results show that the proposed hybrid method quickly reaches all optimal solutions from the literature and in most cases outperforms existing heuristic methods for solving this problem.en
dc.relation.ispartofAnnals of Operations Researchen
dc.subjectEvolutionary methoden
dc.subjectHealth care systemsen
dc.subjectHybrid algorithmen
dc.subjectLocation problemsen
dc.subjectNetwork designen
dc.subjectVariable neighborhood searchen
dc.titleHybrid metaheuristic method for determining locations for long-term health care facilitiesen_US
dc.typeArticleen_US
dc.identifier.doi10.1007/s10479-013-1313-8-
dc.identifier.scopus2-s2.0-84872151684-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/84872151684-
dc.contributor.affiliationInformatics and Computer Scienceen_US
dc.contributor.affiliationNumerical Mathematics and Optimizationen_US
dc.relation.firstpage3en
dc.relation.lastpage23en
dc.relation.volume227en
dc.relation.issue1en
item.fulltextNo Fulltext-
item.openairetypeArticle-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.deptInformatics and Computer Science-
crisitem.author.deptNumerical Mathematics and Optimization-
crisitem.author.orcid0000-0001-7446-0577-
crisitem.author.orcid0000-0001-5658-4111-
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