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dc.contributor.authorXue, N
dc.contributor.authorBai, R
dc.contributor.authorQu, R
dc.contributor.authorAickelin, U
dc.date.accessioned2020-12-01T02:07:48Z
dc.date.available2020-12-01T02:07:48Z
dc.date.issued2020-01-01
dc.identifier.citationXue, N., Bai, R., Qu, R. & Aickelin, U. (2020). A hybrid pricing and cutting approach for the multi-shift full truckload vehicle routing problem. European Journal of Operational Research, 292 (2), https://doi.org/10.1016/j.ejor.2020.10.037.
dc.identifier.issn0377-2217
dc.identifier.urihttp://hdl.handle.net/11343/252710
dc.description.abstractFull truckload transportation (FTL) in the form of freight containers represents one of the most important transportation modes in international trade. Due to large volume and scale, in FTL, delivery time is often less critical but cost and service quality are crucial. Therefore, efficiently solving large scale multiple shift FTL problems is becoming more and more important and requires further research. In one of our earlier studies, a set covering model and a three-stage solution method were developed for a multi-shift FTL problem. This paper extends the previous work and presents a significantly more efficient approach by hybridising pricing and cutting strategies with metaheuristics (a variable neighbourhood search and a genetic algorithm). The metaheuristics were adopted to find promising columns (vehicle routes) guided by pricing and cuts are dynamically generated to eliminate infeasible flow assignments caused by incompatible commodities. Computational experiments on real-life and artificial benchmark FTL problems showed superior performance both in terms of computational time and solution quality, when compared with previous MIP based three-stage methods and two existing metaheuristics. The proposed cutting and heuristic pricing approach can efficiently solve large scale real-life FTL problems.
dc.languageEnglish
dc.publisherElsevier
dc.titleA hybrid pricing and cutting approach for the multi-shift full truckload vehicle routing problem
dc.typeJournal Article
dc.identifier.doi10.1016/j.ejor.2020.10.037
melbourne.affiliation.departmentEngineering and Information Technology
melbourne.affiliation.facultyEngineering and Information Technology
melbourne.source.titleEuropean Journal of Operational Research
melbourne.source.volume292
melbourne.source.issue2
melbourne.elementsid1480979
melbourne.internal.embargodate2022-01-01
melbourne.contributor.authorAickelin, Uwe
dc.identifier.eissn1872-6860
melbourne.accessrightsThis item is embargoed and will be available on 2022-01-01


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