Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/1711
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dc.contributor.authorYağmur, Ece-
dc.contributor.authorKesen, Saadettin Erhan-
dc.date.accessioned2022-01-30T17:32:56Z-
dc.date.available2022-01-30T17:32:56Z-
dc.date.issued2023-
dc.identifier.issn0020-7543-
dc.identifier.issn1366-588X-
dc.identifier.urihttps://doi.org/10.1080/00207543.2021.2017054-
dc.identifier.urihttps://hdl.handle.net/20.500.13091/1711-
dc.description.abstractThis paper studies a new variant of integrated production scheduling and vehicle routing problem where production of customer orders are performed under job-shop environment and order deliveries are made by a heterogeneous fleet of vehicles, each of which is allowed to take multiple trips. Two conflicting objectives are considered, namely minimisation of the total amount of CO2 emitted by the vehicles and minimisation of maximum tardiness resulting from late deliveries. To this end, we present a bi-objective mixed-integer programming formulation. Augmented epsilon-Constraint (Augmecon) method is implemented to find Pareto optimal solutions. Due to problem complexity, Augmecon cannot provide solutions even with small-sized problems. Thus, we adopt Pareto Local Search (PLS) and non-dominated sorting genetic algorithm-II (NSGA-II) for practical sized instances. For small-sized instances involving 5, 6, and 7 customers, experimental results indicate that CPU time of Augmecon are 11, 84, and 524 sec, respectively with an average number of Pareto efficient solution of 3.5. In terms of hypervolume index, Augmecon shows the best performance, followed by NSGA-II with 11.32% and PLS with 20.75% degradation for small-sized instances. For medium and large-sized instances, PLS shows worse performance than NSGA-II by 16.87% and 40.48%.en_US
dc.language.isoenen_US
dc.publisherTaylor & Francis Ltden_US
dc.relation.ispartofInternational Journal Of Production Researchen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectVehicle Routing Problemen_US
dc.subjectJob Shop Schedulingen_US
dc.subjectMixed-Integer Linear Programmingen_US
dc.subjectSustainabilityen_US
dc.subjectNsga-Iien_US
dc.subjectMulti-Objective Optimisationen_US
dc.subjectIntegrated Productionen_US
dc.subjectSupply Chainen_US
dc.subjectRouting Problemen_US
dc.subjectAlgorithmen_US
dc.subjectDeliveryen_US
dc.subjectOptimizationen_US
dc.subjectSearchen_US
dc.subjectModelen_US
dc.titleBi-objective coordinated production and transportation scheduling problem with sustainability: formulation and solution approachesen_US
dc.typeArticleen_US
dc.identifier.doi10.1080/00207543.2021.2017054-
dc.identifier.scopus2-s2.0-85122410446en_US
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.identifier.wosWOS:000739167400001en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.authorscopusid57214825234-
dc.authorscopusid55918231100-
dc.identifier.scopusqualityQ1-
item.openairetypeArticle-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.grantfulltextembargo_20300101-
item.fulltextWith Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.dept02.09. Department of Industrial Engineering-
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections
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