A Constraint Programming model for fast optimal stowage of container vessel bays

Delgado, Alberto; Jensen, Rune Møller; Janstrup, Kira Hyldekær; Rose, Trine Høyer; Andersen, Kent Høj

doi:10.1016/j.ejor.2012.01.028

Cited by 85 publications

(87 citation statements)

References 14 publications

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“…Delgado et al [7] study the stowage planning problem and propose an approach that generates a near optimal plan for a large container vessel within a few minutes. The approach solves the problem in two steps.…”

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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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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“…To deal with the complexity of the CSP, successful studies decompose the problem hierarchically into a multi-port master planning phase and a slot planning phase (Delgado et al, 2012). In the first phase (Master planning), the hatch-overstowage and crane utilization measures are optimized by determining the number of 20ft and 40ft containers that need to be stowed in a location.…”

Section: Stowage Planningmentioning

confidence: 99%

Sea Container Terminals: New Technologies, OR Models, and Emerging Research Areas

2014

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Due to a rapid growth in world trade and a huge increase in containerized goods, sea container terminals play a vital role in globe-spanning supply chains. Container terminals should be able to handle large ships, with large call sizes within the shortest time possible, and at competitive rates. In response, terminal operators, shipping liners, and port authorities are investing in new technologies to improve container handling infrastructure and operational efficiency. Container terminals face challenging research problems which have received much attention from the academic community. The focus of this paper is to highlight the recent developments in the container terminals, which can be categorized into three areas: (1) innovative container terminal technologies, (2) new OR directions and models for existing research areas, and (3) emerging areas in container terminal research. By choosing this focus, we complement existing reviews on container terminal operations.

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“…(Bierwirth and Meisel, 2010)), stowage plans for container vessels (see e.g. (Delgado et al, 2012)) and the container stacking problem (see e.g. (Dekker et al, 2006)).…”

Section: Literature Reviewmentioning

confidence: 99%

A new approach to the Container Positioning Problem

et al. 2015

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In this paper the Container Positioning Problem is revisited. This problem arises at busy container terminals and requires one to minimize the use of block cranes in handling the containers that must wait at the terminal until their next means of transportation. We propose a new Mixed Integer Programming model that not only improves on earlier attempts at this problem, but also better reflects reality. In particular, the proposed model adopts a preference to reshuffle containers in line with a just-in-time concept, as it is assumed that data is more accurate the closer to a container's scheduled departure the time is. Other important improvements include a reduction in the model size, and the ability of the model to consider containers initially at the terminal. In addition, we describe several classes of valid inequalities for this new formulation and present a rolling horizon based heuristic for solving larger instances of the problem. We show that this new formulation drastically outperforms previous attempts at the problem through a direct comparison on instances available in the literature. Furthermore, we also show that the rolling horizon based heuristic can further reduce the solution time on the larger of these instances as well as find acceptable solutions to much bigger, artificially generated, instances.

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A Constraint Programming model for fast optimal stowage of container vessel bays

Cited by 85 publications

References 14 publications

Stowage Planning in Multiple Ports with Shifting Fee Minimization

Stowage Planning in Multiple Ports with Shifting Fee Minimization

Sea Container Terminals: New Technologies, OR Models, and Emerging Research Areas

A new approach to the Container Positioning Problem

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