Weight distribution considerations in container loading

Davies, Arwel; Bischoff, Eberhard E.

doi:10.1016/s0377-2217(98)00139-8

Cited by 160 publications

(97 citation statements)

References 7 publications

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“…Furthermore, researchers have begun paying more attention to additional practical constraints. For instance, Davies and Bischoff [1999], Eley [2002], and Gehring and Bortfeldt [1997] take into account the weight distribution of cargo within a container. Bischoff [2006] examines the impact of varying load bearing strength.…”

Section: Introductionmentioning

confidence: 99%

“…This "wall-building" or "layer-building" method proves to be effective for accommodating other practical container loading constraints such as limited bearing strength [Bischoff, 2006] and weight distributions [Davies and Bischoff, 1999] as well as handling pallet loading problems . Generally speaking, the "wallbuilding" technique treats the remaining space after a wall or layer is loaded as a reduced-sized container with some procedures to fill the trapped or unused space within a layer or across layers.…”

Section: Introductionmentioning

confidence: 99%

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A heuristic for the container loading problem: A tertiary-tree-based dynamic space decomposition approach

Wang

Levy

2008

European Journal of Operational Research

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(2008). A heuristic for the container loading problem: A tertiary-tree-based dynamic space decomposition approach. European Journal of Operational Research, 191 (1) AbstractIncreasing fuel costs, post-911 security concerns, and economic globalization provide a strong incentive for container carriers to use available container space more efficiently, thereby minimizing the number of container trips and reducing socio-economic vulnerability. A heuristic algorithm based on a tertiary tree model is proposed to handle the container loading problem (CLP) with weakly heterogeneous boxes. A dynamic space decomposition method based on the tertiary tree structure is developed to partition the remaining container space after a block of homogeneous rectangular boxes is loaded into a container. This decomposition approach, together with an optimal-fitting sequencing and an inner-right-corner-occupying placement rule, permits a holistic loading strategy to pack a container. Comparative studies with existing algorithms and an illustrative example demonstrate the efficiency of this algorithm.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A heuristic for the container loading problem: A tertiary-tree-based dynamic space decomposition approach

Wang

Levy

2008

European Journal of Operational Research

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“…The rich set of requirements makes CP an attractive modeling approach in this domain [12]. Among the additional requirements, Davies & Bischoff [3] highlight the importance of the weight distribution of the loaded container, focusing on the location of the center of gravity (COG). The exact requirements depend on the specific application, especially on the means of transport.…”

Section: Using Completion M To Solve the Container Loading Problemmentioning

confidence: 99%

“…For container loading with weight distribution considerations, Davies & Bischoff [3] proposed a heuristic that achieves high space utilization combined with an even weight distribution, and claim that the latter leads to a COG located near to the center of the container. Wodziak & Fadel [20] apply a genetic algorithm to minimize the distance of the COG from the desired location in one, two, and two and a half dimensions.…”

Section: Using Completion M To Solve the Container Loading Problemmentioning

confidence: 99%

A Global Constraint for Total Weighted Completion Time

Kovács

Beck

2007

Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems

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The criterion of total weighted completion time occurs as a sub-problem of combinatorial optimization problems in such diverse areas as scheduling, container loading and storage assignment in warehouses. These applications often necessitate considering a rich set of requirements and preferences, which makes constraint programming (CP) an effective modeling and solving approach. On the other hand, basic CP techniques can be inefficient in solving models that require inference over sum type expressions. In this paper, we address increasing the solution efficiency of constraint-based approaches to cumulative resource scheduling with the above criterion. Extending previous results for unary capacity resources, we define the COMPLETION m global constraint for propagating the total weighted completion time of activities that require the same cumulative resource. We present empirical results in two different problem domains: scheduling a single cumulative resource, and container loading with constraints on the location of the center of gravity. In both domains, the proposed constraint propagation algorithm out-performs existing propagation techniques.

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“…Gehring & Bortfeldt (1997) address the problem with several constraints, namely, orientation, load bearing, maximum weight, stability and weight distribution. Davies & Bischoff (1999) propose a heuristic that is able to produce loading arrangements which combine high space utilization with an even weight distribution of the cargo. Bortfeldt et al (2003) and Mack et al (2004) consider constraints of orientation and stability in terms of sections of the cargo that overhang beyond the edge of the box(es) supporting it.…”

Section: Introductionmentioning

confidence: 99%

A multi-start random constructive heuristic for the container loading problem

Araújo

Armentano

2007

Pesqui. Oper.

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This paper deals with the container loading problem which involves the selection of a subset of boxes, each box with a given volume, such that they fit in a single container and maximize its volume utilization subject to orientation and stability constraints. We propose a multi-start random constructive heuristic with a load arrangement that is based on maximal cuboids that fit in given empty spaces. Each instance is adaptively evaluated by a set of criteria, and at each step of the construction process one maximal cuboid is chosen probabilistically from a restricted list of candidates. In order to enhance the flexibility in the construction of a solution, a probabilistic reduction on such cuboids is allowed. Computational tests on several instances from the literature show that the proposed method performs better than other approaches.Keywords: container loading; cuboid arrangement; multi-start random constructive heuristic. ResumoNeste trabalho abordamos o problema de carregamento de contêiner que trata da seleção de um subconjunto de caixas, cada caixa com um dado volume, de forma a maximizar o volume ocupado de um único contêiner sujeito a restrições de orientação e estabilidade. Propomos uma heurística construtiva aleatória com múltiplos inícios que utiliza um arranjo de carga baseado em cubóides que maximizam a ocupação de espaços vazios. Cada instância é avaliada de forma adaptativa por um conjunto de critérios, e em cada passo do processo construtivo um cubóide é selecionado probabilisticamente de uma lista restrita de candidatos. Para aumentar a flexibilidade na construção de uma solução, permite-se uma redução probabilística no tamanho dos cubóides. Resultados computacionais em instâncias da literatura mostram que o método proposto apresenta um desempenho superior a outros enfoques sugeridos na literatura.

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Weight distribution considerations in container loading

Cited by 160 publications

References 7 publications

A heuristic for the container loading problem: A tertiary-tree-based dynamic space decomposition approach

A heuristic for the container loading problem: A tertiary-tree-based dynamic space decomposition approach

A Global Constraint for Total Weighted Completion Time

A multi-start random constructive heuristic for the container loading problem

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