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A new three-step heuristic for the Master Bay Plan Problem

Daniela Ambrosino, Davide Anghinolfi, Massimo Paolucci and Anna Sciomachen
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Daniela Ambrosino: Department of Economics and Quantitative Methods (DiEM), University of Genova, Genova, Italy
Davide Anghinolfi: Department of Communications, Computer and System Sciences (DIST), University of Genova, Genova, Italy
Massimo Paolucci: Department of Communications, Computer and System Sciences (DIST), University of Genova, Genova, Italy
Anna Sciomachen: Department of Economics and Quantitative Methods (DiEM), University of Genova, Genova, Italy

Maritime Economics & Logistics, 2009, vol. 11, issue 1, 98-120

Abstract: In this work, we are looking at the problem of determining stowage plans for containerships. This problem, denoted in the literature as the Master Bay Plan Problem (MBPP), is computationally difficult to solve, that is NP-hard. We start from the optimal solution of subsets of bays related to independent portions of the ship, which are determined by a previously proposed decomposition approach for the MBPP; then, we look for the global ship stability of the overall stowage plan by using a tabu search (TS) meta-heuristic approach. Note that at the same time the proposed TS algorithm allows us to further reduce the handling time of the containers to be loaded on the ship. The proposed heuristics has been implemented within a software support system that helps the planning management in the visualisation of the stowage plans of each bay of the ship. Preliminary computational experimentations performed on some real-life test cases related to a terminal located at the port of Genoa, Italy are provided. Maritime Economics & Logistics (2009) 11, 98–120. doi:10.1057/mel.2008.19

Date: 2009
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Citations: View citations in EconPapers (12)

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