Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/440
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dc.contributor.authorMrkela, Lazaren_US
dc.contributor.authorStanimirović, Zoricaen_US
dc.date.accessioned2022-08-13T09:27:50Z-
dc.date.available2022-08-13T09:27:50Z-
dc.date.issued2019-01-01-
dc.identifier.isbn9783030158422-
dc.identifier.issn03029743en
dc.identifier.urihttps://research.matf.bg.ac.rs/handle/123456789/440-
dc.description.abstractThis paper deals with the Weighted Generalized Regenerator Location Problem (WGRLP) that arises in the design of optical telecommunication networks. During the transmission of optical signal, its quality deteriorates with the distance from the source, and therefore, it has to be regenerated by installing regenerators at some of the nodes in the network. The WGRLP involves weights assigned to potential regenerator locations, reflecting the costs of regenerator deployment. The objective of WGRLP is to minimize the sum of weights assigned to locations with installed regenerators, while ensuring a good quality communication among terminal nodes. As telecommunication networks usually involve large number of nodes, an efficient optimization method is required to deal with real-life problem dimensions. In this paper, a Skewed Variable Neighborhood Search method (SVNS) is proposed as solution approach for the WGRLP. The designed SVNS uses adequate data structures for solution representation and efficient procedures for objective function update, feasibility check, and solution repair. Computational results on the WGRLP data set from the literature show that the proposed SVNS reaches all known optimal solutions on small and medium size instances in short running times and outperforms existing heuristic approaches for the WGRLP. In addition, SVNS is tested on large scale WGRLP instances not considered in the literature so far. The presented computational results indicate the potential of SVNS as solution method for WGRLP and related network design problems.en
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en_US
dc.subjectOptical networksen
dc.subjectSkewed Variable Neighborhood Searchen
dc.subjectTelecommunicationen
dc.subjectWeighted Generalized Regenerator Location Problemen
dc.titleSkewed Variable Neighborhood Search Method for the Weighted Generalized Regenerator Location Problemen_US
dc.typeConference Paperen_US
dc.relation.publicationInternational Conference on Variable Neighborhood Search ICVNS 2018en_US
dc.identifier.doi10.1007/978-3-030-15843-9_15-
dc.identifier.scopus2-s2.0-85064042693-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85064042693-
dc.contributor.affiliationNumerical Mathematics and Optimizationen_US
dc.relation.firstpage182en_US
dc.relation.lastpage201en_US
dc.relation.volume11328 LNCSen_US
item.fulltextNo Fulltext-
item.openairetypeConference Paper-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.deptNumerical Mathematics and Optimization-
crisitem.author.orcid0000-0001-5658-4111-
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