Algorithm selection for the team orienteering problem

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dc.authoridMustafa Mısır / 0000-0002-6885-6775en_US
dc.authorscopusidMustafa Mısır / 36458858100
dc.authorwosidMustafa Mısır / A-6739-2010
dc.contributor.authorMısır, Mustafa
dc.contributor.authorGunawan, Aldy
dc.contributor.authorVansteenwegen, Pieter
dc.date.accessioned2022-06-09T13:41:29Z
dc.date.available2022-06-09T13:41:29Z
dc.date.issued2022en_US
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractThis work utilizes Algorithm Selection for solving the Team Orienteering Problem (TOP). The TOP is an NP-hard combinatorial optimization problem in the routing domain. This problem has been modelled with various extensions to address different real-world problems like tourist trip planning The complexity of the problem motivated to devise new algorithms. However, none of the existing algorithms came with the best performance across all the widely used benchmark instances. This fact suggests that there is a performance gap to fill. This gap can be targeted by developing more new algorithms as attempted by many researchers before. An alternative strategy is performing Algorithm Selection that will automatically choose the most appropriate algorithm for a given problem instance. This study considers the existing algorithms for the Team Orienteering Problem as the candidate method set. For matching the best algorithm with each problem instance, the specific instance characteristics are used as the instance features. An algorithm Selection approach, namely ALORS, is used to conduct the selection mission. The computational analysis based on 157 instances showed that Algorithm Selection outperforms the state-of-the-art algorithms despite the simplicity of the Algorithm Selection setting. Further analysis illustrates the match between certain algorithms and certain instances. Additional analysis showed that the time budget significantly affects the algorithms' performance.en_US
dc.identifier.citationMisir, M., Gunawan, A., Vansteenwegen, P. (2022). Algorithm selection for the team orienteering problem. Evolutionart Computation in Comnibatorial Optimization, Evocop 2022, 13222, 33-45.en_US
dc.identifier.doi10.1007/978-3-031-04148-8_3en_US
dc.identifier.endpage45en_US
dc.identifier.issn0302-9743en_US
dc.identifier.scopus2-s2.0-85128764314en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage33en_US
dc.identifier.urihttps://doi.org/10.1007/978-3-031-04148-8_3
dc.identifier.urihttps://hdl.handle.net/20.500.12713/2853
dc.identifier.volume13222en_US
dc.identifier.wosWOS:000787723000003en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorMısır, Mustafa
dc.language.isoenen_US
dc.publisherSPRINGER-VERLAG BERLINen_US
dc.relation.ispartofEVOLUTIONARY COMPUTATION IN COMBINATORIAL OPTIMIZATION, EVOCOP 2022en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.titleAlgorithm selection for the team orienteering problemen_US
dc.typeConference Objecten_US

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