Performance comparison of approximate dynamic programming techniques for dynamic stochastic scheduling

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dc.authoridYasin Göçgün / 0000-0003-3005-7596en_US
dc.authorscopusidYasin Göçgün / 22634033100
dc.authorwosidYasin Göçgün / IQW-5808-2023
dc.contributor.authorGöçgün, Yasin
dc.date.accessioned2021-06-08T11:17:17Z
dc.date.available2021-06-08T11:17:17Z
dc.date.issued2021en_US
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.description.abstractThis paper focuses on the performance comparison of several approximate dynamic programming (ADP) techniques. In particular, we evaluate three ADP techniques through a class of dynamic stochastic scheduling problems: Lagrangian-based ADP, linear programming-based ADP, and direct search-based ADP. We uniquely implement the direct search-based ADP through basis functions that differ from those used in the relevant literature. The class of scheduling problems has the property that jobs arriving dynamically and stochastically must be scheduled to days in advance. Numerical results reveal that the direct search-based ADP outperforms others in the majority of problem sets generated.en_US
dc.identifier.citationGöçgün, Y. (2021). Performance comparison of approximate dynamic programming techniques for dynamic stochastic scheduling. An International Journal of Optimization and Control: Theories & Applications (IJOCTA), 11(2), 178-185.en_US
dc.identifier.doi10.11121/IJOCTA.01.2021.00987en_US
dc.identifier.endpage185en_US
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85106965075en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage178en_US
dc.identifier.trdizinid491903en_US
dc.identifier.urihttps://doi.org/10.11121/IJOCTA.01.2021.00987
dc.identifier.urihttps://hdl.handle.net/20.500.12713/1786
dc.identifier.volume11en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakTR-Dizinen_US
dc.institutionauthorGöçgün, Yasin
dc.language.isoenen_US
dc.publisherBalikesir Universityen_US
dc.relation.ispartofInternational Journal of Optimization and Control: Theories and Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectApproximate Dynamic Programmingen_US
dc.subjectDynamic Stochastic Schedulingen_US
dc.subjectMarkov Decision Processesen_US
dc.titlePerformance comparison of approximate dynamic programming techniques for dynamic stochastic schedulingen_US
dc.typeArticleen_US

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