A multi product loading problem: a model and a solution method

dc.citation.epage531en_US
dc.citation.issueNumber3en_US
dc.citation.spage519en_US
dc.citation.volumeNumber101en_US
dc.contributor.authorYuceer, U.en_US
dc.date.accessioned2015-07-28T11:55:58Z
dc.date.available2015-07-28T11:55:58Z
dc.date.issued1997en_US
dc.departmentDepartment of Managementen_US
dc.description.abstractAn important operational problem arises during the transportation and delivery of several products, which cannot be mixed, in the same vehicle at regular intervals. The vehicle has compartments to keep the products separately. Therefore, a scheme of allocation of compartments which we call vehicle loading problem to maximize the efficiency of the system while the demands for the products at the destination(s) are satisfied. A mixed binary model is developed for this multi-product loading problem. The solution method is based on simultaneously exploring the primal and dual structures derived from the Lagrangian relaxation. Subset sum problems are obtained as subproblems to the partial Lagrangian. An algorithm is developed and its convergence is proved. The efficiency of the method is demonstrated by running randomly chosen test problems. An initial solution finding method is also developed.en_US
dc.description.provenanceMade available in DSpace on 2015-07-28T11:55:58Z (GMT). No. of bitstreams: 1 10.1016-S0377-2217(96)00185-3.pdf: 952353 bytes, checksum: 26e3dc0c65958fafe6225c6ebf5e7932 (MD5)en
dc.identifier.doi10.1016/S0377-2217(96)00185-3en_US
dc.identifier.issn0377-2217
dc.identifier.urihttp://hdl.handle.net/11693/10814
dc.language.isoEnglishen_US
dc.publisherElsevieren_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/S0377-2217(96)00185-3en_US
dc.source.titleEuropean Journal of Operational Researchen_US
dc.subjectMathematical programmingen_US
dc.subjectLagrangian relaxationen_US
dc.subjectDistributionen_US
dc.subjectSet partitioningen_US
dc.titleA multi product loading problem: a model and a solution methoden_US
dc.typeArticleen_US

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