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

Ambrosino, Daniela; Anghinolfi, Davide; Paolucci, Massimo; Sciomachen, Anna

doi:10.1057/mel.2008.19

Cited by 39 publications

(23 citation statements)

References 19 publications

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“…Focusing on a single port problem with heuristic stability rules and a mixture of container types, Ambrosino, Sciomachen, and Tanfani (2004) proposed a binary formulation for the master bay planning problem (MBPP). The problem is solved using a heuristic preprocessing procedure, which is then extended to a three-phase heuristic by Ambrosino, Sciomachen, and Tanfani (2006) and then further combined with a tabu search by Ambrosino et al (2009). The relation between the MBPP and the 3-Dimensional Bin Packing Problem is studied by Tanfani (2003, 2007), where the ship is seen as the only available bin.…”

Section: Literature On Rich Stowage Planning Problemsmentioning

confidence: 99%

A Decomposition Method for Finding Optimal Container Stowage Plans

Roberti

Pacino

2018

Transportation Science

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In transportation of goods in large container ships, shipping industries need to minimize the time spent at ports to load/unload containers. An optimal stowage of containers on board minimizes unnecessary unloading/reloading movements, while satisfying many operational constraints. We address the basic container stowage planning problem (CSPP). Different heuristics and formulations have been proposed for the CSPP, but finding an optimal stowage plan remains an open problem even for small-sized instances. We introduce a novel formulation that decomposes CSPPs into two sets of decision variables: the first defining how single container stacks evolve over time and the second modeling port-dependent constraints. Its linear relaxation is solved through stabilized column generation and with different heuristic and exact pricing algorithms. The lower bound achieved is then used to find an optimal stowage plan by solving a mixed-integer programming model. The proposed solution method outperforms the methods from the literature and can solve to optimality instances with up to 10 ports and 5,000 containers in a few minutes of computing time.

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Section: Literature On Rich Stowage Planning Problemsmentioning

confidence: 99%

A Decomposition Method for Finding Optimal Container Stowage Plans

Roberti

Pacino

2018

Transportation Science

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“…Ambrosino et al [9] study the Master Bay Plan Problem (MBPP) and propose a tabu search metaheuristic approach to look for the global ship stability of the overall stowage plan. The proposed tabu search algorithm can improve planning management in the visualization of stowage plans in a software support system.…”

Section: Stowage Planning In Singlementioning

confidence: 99%

Stowage Planning in Multiple Ports with Shifting Fee Minimization

Zhang

Qihuang

Liu

et al. 2018

Scientific Programming

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This paper studies the problem of stowage planning within a vessel bay in a multiple port transportation route, aiming at minimizing the total container shifting fee. Since the access to containers is in the top-to-bottom order for each stack, reshuffle operations occur when a target container to be unloaded at its destination port is not stowed on the top of a stack at the time. Each container shift via a quay crane induces one unit of shifting fee that depends on the charge policy of the local container port. Previous studies assume that each container shift consumes a uniform cost in all ports and thus focus on minimizing the total number of shifts or the turnaround time of the vessel. Motivated by the observation that different ports are of nonuniform fee for each container shift, we propose a mixed integer programming (MIP) model for the problem to produce an optimal stowage planning with minimum total shifting fee in this work. Moreover, as the considered problem is NP-hard due to the NP-hardness of its counterpart with uniform unit shifting fee, we propose an improved genetic algorithm to solve the problem. The efficiency of the proposed algorithm is demonstrated via numerical experiments.

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“…Both Kang and Kim (2002) and Wilson and Roach (2000) describes a 2phased approach, where the former is of an iterative nature, and in the latter the flow of information only goes downward. A three-step heuristic is introduced in Ambrosino et al (2009), in which the left and right, and bow and stern weight differences are kept within a tolerance. Pacino et al (2011) presents a solution method which takes most of the stability issues into consideration.…”

Section: Literature Reviewmentioning

confidence: 99%

A matheuristic for the Cargo Mix Problem with Block Stowage

Christensen

Pacino

2017

Transportation Research Part E: Logistics and Transportation Re

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

Cited by 39 publications

References 19 publications

A Decomposition Method for Finding Optimal Container Stowage Plans

A Decomposition Method for Finding Optimal Container Stowage Plans

Stowage Planning in Multiple Ports with Shifting Fee Minimization

A matheuristic for the Cargo Mix Problem with Block Stowage

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