A multi-faced buildup algorithm for three-dimensional packing problems

Lim, Andrew; Rodrigues, Brian; Wang, Y.

doi:10.1016/j.omega.2003.08.004

Cited by 53 publications

(25 citation statements)

References 18 publications

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“…Such a representation is used by , Chien & Deng (2004) and an adaptation of the representation is utilized by Bischoff (2006). Lim et al (2003) propose a heuristic in which the walls of the container are used as the ground to build up a load arrangement, called multifaced buildup.…”

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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Section: Introductionmentioning

confidence: 99%

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

Araújo

Armentano

2007

Pesqui. Oper.

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“…It takes 0.22 to 2.7 seconds to pack one container, except 4.22 seconds for the 45th case and 11 seconds for the 46th case. Note that in [4], the authors did not compute the 45th to the 47th cases. Figure 9 refers to the volume utilization of algorithm B 2 , where x-axis represents the test case index and y-axis represents the container volume utilization.…”

Section: Resultsmentioning

confidence: 99%

“…Basic methods are wall building [1,3,4], layering [5], guillotine cutting [6], block arrangement [7,8,9], etc. Tree-search [1,7], tabu search [8], simulated annealing [8], or genetic search [9] is incorporated to improve the solution's quality.…”

Section: Introductionmentioning

confidence: 99%

“…Sometimes, parallel methods are used to shorten the computation time [8,9]. Based on the wall building and layering methods, Lim et al proposed a basic algorithm MFB and a strengthened algorithm MFB_L [4]. They tested on 760 benchmarks from the ORLibrary [10].…”

Section: Introductionmentioning

confidence: 99%

“…We tested our algorithm using all the 47 benchmarks from the OR-Library [10] that allow rotations. Results generated are compared with those in [4] which tested the same data. Experiments indicate that we are able to achieve an average packing utilization of 94.6%.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Efficient Algorithm for Solving the Container Loading Problem

Huang

Combinatorics, Algorithms, Probabilistic and Experimental Methodologies

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Abstract. We present a new algorithm for the three-dimensional packing problem with a single container to be loaded. Deviates from the traditional approaches, it uses a principle --"largest caving degree" such that items are packed as closely as possible. Then, it incorporates a backtracking strategy that gains a good trade-off between solution quality and computation time. We tested our algorithm using all the 47 related benchmarks from the OR-Library that have no orientation constraints. Experiments indicate the algorithm's good quality. The container volume utilization, achieved within comparable time, is 94.6% on average. This significantly improves current best-known results in the literature by 3.6%.

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A Review of the Solutions for the Container Loading Problem, and the Use of Heuristics

Aydemir

Yi̇ği̇t

2020

Artificial Intelligence and Applied Mathematics in Engineering Problems

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A multi-faced buildup algorithm for three-dimensional packing problems

Cited by 53 publications

References 18 publications

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

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

An Efficient Algorithm for Solving the Container Loading Problem

A Review of the Solutions for the Container Loading Problem, and the Use of Heuristics

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