Traveling repairmen problem: A biogeography-based optimization

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buir.contributor.authorKarasan, Oya Ekin
dc.citation.epage515en_US
dc.citation.spage506en_US
dc.citation.volumeNumber1en_US
dc.contributor.authorÖder Uzun, G.
dc.contributor.authorDengiz, B.
dc.contributor.authorKara, İ.
dc.contributor.authorKarasan, Oya Ekin
dc.contributor.editorXu, Jiuping
dc.contributor.editorAltıparmak, Fulya
dc.contributor.editorHassan, Mohamed Hag Ali
dc.contributor.editorMárquez, Fausto Pedro García
dc.contributor.editorHajiyev, Asaf
dc.coverage.spatialAnkara, Turkeyen_US
dc.date.accessioned2023-02-15T11:21:24Z
dc.date.available2023-02-15T11:21:24Z
dc.date.issued2022-07-14
dc.departmentDepartment of Industrial Engineeringen_US
dc.descriptionConference Name: ICMSEM 2022: Proceedings of the Sixteenth International Conference on Management Science and Engineering Managementen_US
dc.descriptionDate of Conference: 3-6 August 2022en_US
dc.description.abstractTraveling Repairman Problem (TRP), which is also known by names cumulative traveling salesman problem, the deliveryman prob lem and the minimum latency problem, is a special variant of Traveling Salesman Problem (TSP). In contrast to the minimization of completion time objective of TSP, the desired objective of TRP is to minimize the cumulative latency (waiting time or delay time) of all customers. In this paper, a generalized version of TRP with multi depots and time windows, namely Multi Depot Traveling Repairman Problem with Time Windows (MDTRPTW) is considered. A group of homogeneous repairmen initi ate and finish their visit tours at multiple depots. Each customer must be visited exactly by one repairman within their provided earliest end latest times. Being a challenging Nondeterministic Polynomial-hard (NP hard) optimization problem, exact solution approaches are not expected to scale to realistic dimensions of MDTRPTW. Thus, we propose a biogeography-based optimization algorithm (BBOA) as a metaheuristic approach to solve large size MDTRPTW problems. The proposed meta heuristic is analyzed in terms of solution quality, coefficient of variation as well as computation time by solving some test problems adapted from the related literature. The efficacy of the proposed solution methodology is demonstrated by solving instances with 288 customers within seconds.en_US
dc.identifier.doi10.1007/978-3-031-10388-9_37en_US
dc.identifier.eisbn978-3-031-10388-9
dc.identifier.isbn978-3-031-10387-2
dc.identifier.urihttp://hdl.handle.net/11693/111338
dc.language.isoEnglishen_US
dc.publisherSpringer Chamen_US
dc.relation.ispartofseriesLecture Notes on Data Engineering and Communications Technologies;
dc.relation.isversionofhttps://doi.org/10.1007/978-3-031-10388-9_37en_US
dc.source.titleProceedings of the sixteenth international conference on management science and engineering managementen_US
dc.subjectTraveling salesman problemen_US
dc.subjectHeuristic algorithmsen_US
dc.subjectLogistics problemsen_US
dc.subjectRoutingen_US
dc.titleTraveling repairmen problem: A biogeography-based optimizationen_US
dc.typeConference Paperen_US

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