Please use this identifier to cite or link to this item: http://doi.org/10.25358/openscience-7216
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dc.contributor.authorHeßler, Katrin-
dc.contributor.authorIrnich, Stefan-
dc.contributor.authorKreiter, Tobias-
dc.contributor.authorPferschy, Ulrich-
dc.date.accessioned2022-06-27T08:55:53Z-
dc.date.available2022-06-27T08:55:53Z-
dc.date.issued2022-
dc.identifier.urihttps://openscience.ub.uni-mainz.de/handle/20.500.12030/7230-
dc.description.abstractWe consider a packing problem that arises in a direct-shipping system in the food and beverage industry: Trucks are the containers, and products to be distributed are the items. The packing is constrained by two independent quantities, weight (e.g., measured in kg) and volume (number of pallets). Additionally, the products are grouped into the three categories: standard, cooled, and frozen (the latter two require refrigerated trucks). Products of different categories can be transported in one truck using separated zones, but the cost of a truck depends on the transported product categories. Moreover, splitting orders of a product should be avoided so that (un-)loading is simplified. As a result, we seek for a feasible packing optimizing the following objective functions in a strictly lexicographic sense: minimize the (1) total number of trucks; (2) number of refrigerated trucks; (3) number of refrigerated trucks which contain frozen products; (4) number of refrigerated trucks which also transport standard products; (5) and minimize splitting. This is a real-world application of a bin-packing problem with cardinality constraints a.k.a. the two-dimensional vector packing problem with additional constraints. We provide a heuristic and an exact solution approach. The heuristic meta-scheme considers the multi-compartment and item fragmentation features of the problem and applies various problem-specific heuristics. The exact solution algorithm covering all five stages is based on branch-and-price using stabilization techniques exploiting dual-optimal inequalities. Computational results on real-world and difficult self-generated instances prove the applicability of our approach.en_GB
dc.language.isoengde
dc.rightsCC BY*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subject.ddc330 Wirtschaftde_DE
dc.subject.ddc330 Economicsen_GB
dc.subject.ddc650 Managementde_DE
dc.subject.ddc650 Management and auxiliary servicesen_GB
dc.titleBin packing with lexicographic objectives for loading weight- and volume-constrained trucks in a direct-shipping systemen_GB
dc.typeZeitschriftenaufsatzde
dc.identifier.doihttp://doi.org/10.25358/openscience-7216-
jgu.type.dinitypearticleen_GB
jgu.type.versionPublished versionde
jgu.type.resourceTextde
jgu.organisation.departmentFB 03 Rechts- und Wirtschaftswissenschaftende
jgu.organisation.number2300-
jgu.organisation.nameJohannes Gutenberg-Universität Mainz-
jgu.rights.accessrightsopenAccess-
jgu.journal.titleOR spectrumde
jgu.journal.volume44de
jgu.journal.issue2de
jgu.pages.start375de
jgu.pages.end417de
jgu.publisher.year2022-
jgu.publisher.nameSpringerde
jgu.publisher.placeBerlin u.a.de
jgu.publisher.issn1436-6304de
jgu.organisation.placeMainz-
jgu.subject.ddccode330de
jgu.subject.ddccode650de
jgu.publisher.doi10.1007/s00291-021-00628-xde
jgu.organisation.rorhttps://ror.org/023b0x485
Appears in collections:JGU-Publikationen

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