Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/467
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dc.contributor.authorDražić, Zoricaen_US
dc.date.accessioned2022-08-13T09:44:33Z-
dc.date.available2022-08-13T09:44:33Z-
dc.date.issued2016-01-01-
dc.identifier.issn03540243en
dc.identifier.urihttps://research.matf.bg.ac.rs/handle/123456789/467-
dc.description.abstractThis paper presents new modifications of Variable Neighborhood Search approach for solving the file transfer scheduling problem. To obtain better solutions in a small neighborhood of a current solution, we implement two new local search procedures. As Gaussian Variable Neighborhood Search showed promising results when solving continuous optimization problems, its implementation in solving the discrete file transfer scheduling problem is also presented. In order to apply this continuous optimization method to solve the discrete problem, mapping of uncountable set of feasible solutions into a finite set is performed. Both local search modifications gave better results for the large size instances, as well as better average performance for medium and large size instances. One local search modification achieved significant acceleration of the algorithm. The numerical experiments showed that the results obtained by Gaussian modifications are comparable with the results obtainedby standard VNS based algorithms, developed for combinatorial optimization. In some cases Gaussian modifications gave even better results.en
dc.relation.ispartofYugoslav Journal of Operations Researchen
dc.subjectCombinatorial optimizationen
dc.subjectFile transfer scheduling problemen
dc.subjectGaussian Variable Neighborhood Searchen
dc.subjectVariable Neighborhood Searchen
dc.titleGaussian Variable Neighborhood Search for the file transfer scheduling problemen_US
dc.typeArticleen_US
dc.identifier.doi10.2298/YJOR150124006D-
dc.identifier.scopus2-s2.0-84974603516-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/84974603516-
dc.contributor.affiliationNumerical Mathematics and Optimizationen_US
dc.relation.firstpage173en
dc.relation.lastpage188en
dc.relation.volume26en
dc.relation.issue2en
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.openairetypeArticle-
crisitem.author.deptNumerical Mathematics and Optimization-
crisitem.author.orcid0000-0002-3434-6734-
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