Abstract
In this paper we present a Benders decomposition approach for the Berth Allocation Problem (BAP). Benders decomposition is a cutting plane method that has been widely used for solving large-scale mixed integer linear optimization problems. On the other hand, the Berth Allocation Problem is a NP-hard and large-scale problem that has been gaining relevance both from the practical and scientific points of view. In this work we address the discrete and dynamic version of the problem, and develop a new decomposition approach and apply it to a reformulation of the BAP based on the Heterogeneous Vehicle Routing Problem with Time Windows (HVRPTW) model. In a discrete and dynamic BAP each berth can moor one vessel at a time, and the vessels are not all available to moor at the beginning of the planning horizon (there is an availability time window). Computational tests are run to compare the proposed Benders Decomposition with a state-of-the-art commercial solver.
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Acknowledgements
The authors acknowledge the Project “TEC4Growth—Pervasive Intelligence, Enhancers and Proofs of Concept with Industrial Impact/NORTE-01-0145-FEDER-000020” is financed by the North Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF).
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Supplementary material: Computational results.
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Barbosa, F., Oliveira, J.F., Carravilla, M.A., Curcio, E.F. (2019). A Benders Decomposition Algorithm for the Berth Allocation Problem. In: Alves, M., Almeida, J., Oliveira, J., Pinto, A. (eds) Operational Research. IO 2018. Springer Proceedings in Mathematics & Statistics, vol 278. Springer, Cham. https://doi.org/10.1007/978-3-030-10731-4_3
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