A conditional β -mean approach to risk-averse stochastic multiple allocation hub location problems

buir.contributor.authorYetiş Kara, Bahar
buir.contributor.orcidYetiş Kara, Bahar|0000-0001-8674-1165
dc.citation.epage102602- 24en_US
dc.citation.spage102602- 1en_US
dc.citation.volumeNumber158en_US
dc.contributor.authorGhaffarinasab, N.
dc.contributor.authorYetiş Kara, Bahar
dc.date.accessioned2023-02-16T11:37:42Z
dc.date.available2023-02-16T11:37:42Z
dc.date.issued2022-01-29
dc.departmentDepartment of Industrial Engineeringen_US
dc.description.abstractThis paper addresses risk-averse stochastic hub location problems where the risk is measured using the conditional β -mean criterion. Three variants of the classical multiple allocation hub location problem, namely the p-hub median, the p-hub maximal covering, and the weighted p-hub center problems are studied under demand data uncertainty represented by a finite set of scenarios. Novel mixed-integer linear programming formulations are proposed for the problems and exact algorithms based on Benders decomposition are developed for solving large instances of the problems. A large set of computational tests are conducted so that the efficiency of the proposed algorithms is proved and the effect of various input parameters on the optimal solutions is analyzed.en_US
dc.embargo.release2024-01-29
dc.identifier.doi10.1016/j.tre.2021.102602en_US
dc.identifier.eissn1878-5794
dc.identifier.issn1366-5545
dc.identifier.urihttp://hdl.handle.net/11693/111451
dc.language.isoEnglishen_US
dc.publisherElsevier Ltden_US
dc.relation.isversionofhttps://doi.org/10.1016/j.tre.2021.102602en_US
dc.source.titleTransportation Research Part E: Logistics and Transportation Reviewen_US
dc.subjectHub locationen_US
dc.subjectConditional β-meanen_US
dc.subjectMathematical formulationen_US
dc.subjectBenders decompositionen_US
dc.titleA conditional β -mean approach to risk-averse stochastic multiple allocation hub location problemsen_US
dc.typeArticleen_US
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