METAHEURISTIČKE METODE VIŠEKRITERIJUMSKE OPTIMIZACIJE I PRIMENE NA DISKRETNE LOKACIJSKE PROBLEME

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METAHEURISTIČKE METODE VIŠEKRITERIJUMSKE OPTIMIZACIJE I PRIMENE NA DISKRETNE LOKACIJSKE PROBLEME

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dc.contributor.advisor Stanimirović, Zorica
dc.contributor.author Mrkela, Lazar
dc.date.accessioned 2025-02-06T13:58:06Z
dc.date.available 2025-02-06T13:58:06Z
dc.date.issued 2024
dc.identifier.uri http://hdl.handle.net/123456789/5750
dc.description.abstract This dissertation examines two discrete location problems and their bi- objective variants. The first problem under consideration is the maximal covering location problem with user preferences and budget constraints imposed on facility opening. This variant of the maximal covering problem has not been previously studied in the literature. Unlike the classical maximal covering problem, the variant proposed in this dissertation includes user preferences for locations, where users are assigned to the location with opened facility that they prefer the most. Additionally, different locations have different costs for establishing facilities, and the available budget for opening facilities is limited. This problem is solved using the Variable Neighborhood Search (VNS) method, and the results were compared with the ones obtained by an exact solver on modified instances from the literature. Furthermore, an existing variant of the maximal covering problem is also addressed, which imposes the limit on the number of opened facilities instead of limiting the budget for opening facilities. The second problem examined is the regenerator placement in optical networks. In optical networks, signal quality degrades with distance, necessitating the place- ment of costly devices to restore the signal. This dissertation studies an existing model where the set of possible regenerator locations and the set of user nodes are different, defining the problem as generalized. The generalized regenerator place- ment problem in optical networks is also solved using the Variable Neighborhood Search method, with results compared to the best available solutions from the lit- erature. Bi-objective variants of these problems are defined as well. For the maximal covering location problem, user preferences are included as weighted factors in the total covered demand, forming the first objective function. The second objective function represents the number of uncovered users and aims to ensure fairness in the model. In the regenerator placement problem for optical networks, it is assumed that, due to budget constraints, uninterrupted communication between all pairs of user nodes may not be feasible. Each pair is assigned a weight, and the sum of the weights of connected pairs constitutes the first objective function, while the second objective function represents the cost of placing regenerators. These bi-objective variants are solved using an adapted multi-objective version of the Variable Neigh- borhood Search method, and the results are compared with general evolutionary algorithms. en_US
dc.description.provenance Submitted by Slavisha Milisavljevic (slavisha) on 2025-02-06T13:58:05Z No. of bitstreams: 1 lazar_mrkela_doktorska_disertacija.pdf: 17560846 bytes, checksum: 2f957300ae956b81f4495cd1e8e41652 (MD5) en
dc.description.provenance Made available in DSpace on 2025-02-06T13:58:06Z (GMT). No. of bitstreams: 1 lazar_mrkela_doktorska_disertacija.pdf: 17560846 bytes, checksum: 2f957300ae956b81f4495cd1e8e41652 (MD5) Previous issue date: 2024 en
dc.language.iso sr en_US
dc.publisher Beograd en_US
dc.title METAHEURISTIČKE METODE VIŠEKRITERIJUMSKE OPTIMIZACIJE I PRIMENE NA DISKRETNE LOKACIJSKE PROBLEME en_US
mf.author.birth-date 1992-08-03
mf.author.birth-place Knin en_US
mf.author.birth-country Hrvatska en_US
mf.author.residence-state Srbija en_US
mf.author.citizenship Srpsko en_US
mf.author.nationality Srbin en_US
mf.subject.area Computer Science en_US
mf.subject.keywords multi-objective optimisation, maximal covering location problem, re- generator location problem, metaheuristics, variable neighborhood search, evolu- tionary algorithms en_US
mf.subject.subarea Computational Intelligence en_US
mf.contributor.committee Marić, Miroslav
mf.contributor.committee Radojičić Matić, Nina
mf.contributor.committee Davidović, Tatjana
mf.university.faculty Mathematical Faculty en_US
mf.document.references 188 en_US
mf.document.pages 157 en_US
mf.document.genealogy-project No en_US
mf.university Belgrade University en_US

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