Abstract
In this paper, we describe a set of algorithms regarding real combinatorial optimization problems in the context of transportation of goods. These problems consist in the combination of the vehicle routing problem with the two-dimensional bin-packing problem, which is also known as the vehicle routing problem with two-dimensional loading constraints. We also analyzed two related problems, namely the elementary shortest path problem and the vehicle routing problem with mixed linehaul and backhaul customers. In both problems, two-dimensional loading constraints are explicitly considered. Two column generation based approaches are proposed for the vehicle routing problem with two-dimensional constraints. The elementary shortest path problem with two-dimensional constraints is addressed due to its importance in solving the subproblem of the column generation algorithms. To the best of our knowledge, we contribute with the first approach for this problem, through different constructive strategies to achieve feasible solutions, and a variable neighborhood search algorithm in order to search for improved solutions. In what concerns the vehicle routing problem with mixed linehaul and backhaul customers and two-dimensional loading constraints, different variable neighborhood search algorithms are proposed. All the proposed methods were implemented and experimentally tested. An exhaustive set of computational tests was conducted, using, for this purpose, a large group of benchmark instances. In some cases, a large set of benchmark instances was adapted in order to assess the quality of the proposed models.
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Acknowledgements
This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT—Fundação para a Ciência e Tecnologia within the Project Scope: UID/ CEC/00319/2013, and through the grant SFRH/BD/73584/2010, funded by QREN - POPH - Typology 4.1 - co-funded by the European Social Fund.
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Pinto, T., Alves, C., Valério de Carvalho, J. (2018). Models and Advanced Optimization Algorithms for the Integrated Management of Logistics Operations. In: Vaz, A., Almeida, J., Oliveira, J., Pinto, A. (eds) Operational Research. APDIO 2017. Springer Proceedings in Mathematics & Statistics, vol 223. Springer, Cham. https://doi.org/10.1007/978-3-319-71583-4_21
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