Please use this identifier to cite or link to this item:
https://research.matf.bg.ac.rs/handle/123456789/446
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Marić, Miroslav | en_US |
dc.contributor.author | Stanimirović, Zorica | en_US |
dc.contributor.author | Božović, Srdjan | en_US |
dc.date.accessioned | 2022-08-13T09:27:51Z | - |
dc.date.available | 2022-08-13T09:27:51Z | - |
dc.date.issued | 2015-04-01 | - |
dc.identifier.issn | 02545330 | en |
dc.identifier.uri | https://research.matf.bg.ac.rs/handle/123456789/446 | - |
dc.description.abstract | Long-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.ispartof | Annals of Operations Research | en |
dc.subject | Evolutionary method | en |
dc.subject | Health care systems | en |
dc.subject | Hybrid algorithm | en |
dc.subject | Location problems | en |
dc.subject | Network design | en |
dc.subject | Variable neighborhood search | en |
dc.title | Hybrid metaheuristic method for determining locations for long-term health care facilities | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1007/s10479-013-1313-8 | - |
dc.identifier.scopus | 2-s2.0-84872151684 | - |
dc.identifier.url | https://api.elsevier.com/content/abstract/scopus_id/84872151684 | - |
dc.contributor.affiliation | Informatics and Computer Science | en_US |
dc.contributor.affiliation | Numerical Mathematics and Optimization | en_US |
dc.relation.firstpage | 3 | en |
dc.relation.lastpage | 23 | en |
dc.relation.volume | 227 | en |
dc.relation.issue | 1 | en |
item.fulltext | No Fulltext | - |
item.openairetype | Article | - |
item.grantfulltext | none | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
crisitem.author.dept | Informatics and Computer Science | - |
crisitem.author.dept | Numerical Mathematics and Optimization | - |
crisitem.author.orcid | 0000-0001-7446-0577 | - |
crisitem.author.orcid | 0000-0001-5658-4111 | - |
Appears in Collections: | Research outputs |
SCOPUSTM
Citations
15
checked on Nov 8, 2024
Page view(s)
9
checked on Nov 15, 2024
Google ScholarTM
Check
Altmetric
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.