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dc.contributor.authorOstojić, Dragutin-
dc.contributor.authorDavidović, Tatjana-
dc.contributor.authorJakšić Krüger, Tatjana-
dc.contributor.authorRamljak, Dušan-
dc.date.accessioned2023-03-29T10:17:50Z-
dc.date.available2023-03-29T10:17:50Z-
dc.date.issued2022-
dc.identifier.isbn978-989-758-548-7en_US
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/17514-
dc.description.abstractCloud computing, new paradigms like fog, edge computing, require revisiting scheduling and resource allocation problems. Static scheduling of independent tasks on identical processors, one of the simplest scheduling problems, has regained importance and we aim to find stochastic iterative heuristic algorithms to efficiently deal with it. Combining various actions to define solution transformations to improve solution quality, we created 35 heuristic algorithms. To investigate the performance of the proposed approaches, extensive numerical experiments are performed on hard benchmark instances. Among the tested variants, we identified the best performing ones with respect to the solution quality, running time, and stability.en_US
dc.description.sponsorshipThis work was partially supported by the Science Fund of Republic of Serbia AI4TrustBC project and by the Serbian Ministry of Education, Science and Technological Development, Agreement No. 451-03-9/2021-14/200029. The authors thank Penn State GV IT team for the support.en_US
dc.publisherSciTePressen_US
dc.rightsinfo:eu-repo/semantics/openAccess-
dc.source11th International Conference on Operations Research and Enterprise Systems, ICORES 2022, (virtual), Feb. 3-5, 2022en_US
dc.subjectScheduling Problemsen_US
dc.subjectIdentical Processorsen_US
dc.subjectStochastic Heuristicsen_US
dc.subjectSolution Transformationen_US
dc.titleComparative Analysis of Heuristic Approaches to P||Cmaxen_US
dc.typearticleen_US
dc.identifier.doi10.5220/0011008500003117en_US
Налази се у колекцијама:Faculty of Science, Kragujevac

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