Relevant bibliographies by topics / Container loading problem

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Container loading problem'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Container loading problem"

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Pisinger, David. "Heuristics for the container loading problem." European Journal of Operational Research 141, no. 2 (September 2002): 382–92. http://dx.doi.org/10.1016/s0377-2217(02)00132-7.

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MOHAMMED, SHARIF, HUSAIN AZHAR, LATEEF MOHAMMED, and DAYOUB M. "Optimization of Makespan of Container Loading -Unloading Problem Using Mixed Integer Programming." International Journal of Earth Sciences and Engineering 10, no. 01 (March 6, 2017): 53–57. http://dx.doi.org/10.21276/ijee.2017.10.0108.

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Mohamed. "Ant Colony Optimization for Container Loading Problem." Journal of Mathematics and Statistics 8, no. 2 (February 1, 2012): 169–75. http://dx.doi.org/10.3844/jmssp.2012.169.175.

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Hifi, M. "Approximate algorithms for the container loading problem." International Transactions in Operational Research 9, no. 6 (November 2002): 747–74. http://dx.doi.org/10.1111/1475-3995.00386.

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Tian, Tian, Wenbin Zhu, Andrew Lim, and Lijun Wei. "The multiple container loading problem with preference." European Journal of Operational Research 248, no. 1 (January 2016): 84–94. http://dx.doi.org/10.1016/j.ejor.2015.07.002.

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Che, Chan Hou, Weili Huang, Andrew Lim, and Wenbin Zhu. "The multiple container loading cost minimization problem." European Journal of Operational Research 214, no. 3 (November 2011): 501–11. http://dx.doi.org/10.1016/j.ejor.2011.04.017.

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Torra, Vicenç, and Sadaaki Miyamoto. "Container Loading for Nonorthogonal Objects: Detecting Collisions." Journal of Advanced Computational Intelligence and Intelligent Informatics 12, no. 5 (September 20, 2008): 422–25. http://dx.doi.org/10.20965/jaciii.2008.p0422.

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This paper considers the problem of container loading. That is, the problem of locating a predefined set of objects into containers so that the number of containers is minimized. In this paper we outline our system, which includes as a distinguished aspect the possibility of considering objects that are nonorthogonal. That is, non rectangular objects are permitted to be located in the container.
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Scheithauer, G. "LP-based bounds for the container and multi-container loading problem." International Transactions in Operational Research 6, no. 2 (March 1999): 199–213. http://dx.doi.org/10.1111/j.1475-3995.1999.tb00151.x.

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Ramos, A. Galrão, José F. Oliveira, José F. Gonçalves, and Manuel P. Lopes. "Dynamic stability metrics for the container loading problem." Transportation Research Part C: Emerging Technologies 60 (November 2015): 480–97. http://dx.doi.org/10.1016/j.trc.2015.09.012.

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Moura, A., and J. F. Oliveira. "A GRASP Approach to the Container-Loading Problem." IEEE Intelligent Systems 20, no. 4 (July 2005): 50–57. http://dx.doi.org/10.1109/mis.2005.57.

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Dissertations / Theses on the topic "Container loading problem"

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Zhao, Xiaozhou. "The three-dimensional container loading problem." Thesis, University of Southampton, 2017. https://eprints.soton.ac.uk/413542/.

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This thesis investigates the three-dimensional container loading problem. We review all literatures published in this area, and explain our unique problem raised from an industry partner. As constructive heuristic remains uncontrollable to us, we design improvement algorithms both to and not to intervene with how constructive heuristic works, namely iterated local search and beam search. New benchmark data sets for multiple containers problem are generated to fill the shortage of challenging data sets. Computational results for homogeneous containers problem indicate that while both approaches work on our problem, beam search remains a favourable choice. We also extend our algorithms to solve heterogeneous containers problem.
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Koo, Wai-yip. "Container loading problem by a multi-stage heuristics approach /." Hong Kong : University of Hong Kong, 1997. http://sunzi.lib.hku.hk/hkuto/record.jsp?B19471245.

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古偉業 and Wai-yip Koo. "Container loading problem by a multi-stage heuristics approach." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1997. http://hub.hku.hk/bib/B31215397.

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Olsson, Jonas. "Solving a highly constrained multi-level container loading problem from practice." Thesis, Linköpings universitet, Optimeringslära, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-134430.

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The container loading problem considered in this thesis is to determine placements of a set of packages within one or multiple shipping containers. Smaller packages are consolidated on pallets prior to being loaded in the shipping containers together with larger packages. There are multiple objectives which may be summarized as fitting all the packages while achieving good stability of the cargo as well as the shipping containers themselves. According to recent literature reviews, previous research in the field have to large extent been neglecting issues relevant in practice. Our real-world application was developed for the industrial company Atlas Copco to be used for sea container shipments at their Distribution Center (DC) in Texas, USA. Hence all applicable practical constraints faced by the DC operators had to be treated properly. A high variety in sizes, weights and other attributes such as stackability among packages added complexity to an already challenging combinatorial problem. Inspired by how the DC operators plan and perform loading manually, the batch concept was developed, which refers to grouping of boxes based on their characteristics and solving subproblems in terms of partial load plans. In each batch, an extensive placement heuristic and a load plan evaluation run iteratively, guided by a Genetic Algorithm (GA). In the placement heuristic, potential placements are evaluated using a scoring function considering aspects of the current situation, such as space utilization, horizontal support and heavier boxes closer to the floor. The scoring function is weighted by coefficients corresponding to the chromosomes of an individual in the GA population. Consequently, the fitness value of an individual in the GA population is the rating of a load plan. The loading optimization software has been tested and successfully implemented at the DC in Texas. The software has been proven capable of generating satisfactory load plans within acceptable computation times, which has resulted in reduced uncertainty and labor usage in the loading process. Analysis using real sea container shipments shows that the GA is able to tune the scoring coefficients to suit the particular problem instance being solved.
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Araujo, Luiz Jonatã Pires de. "A hybrid methodology to solve the container loading problem with weight distribution and cutting problems." Universidade de Fortaleza, 2011. http://dspace.unifor.br/handle/tede/88221.

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Transport of goods has represented an important role in economic development throughout the history and ship containerization brought great advantages. Its invention in mid-1950s brought down the cost of transport and reduced time for loading and unloading cargo. Consequently, it increased efficiency of port working and reduced handling cargo to hours instead of weeks, as before. However, the good use of containerization involves new and specialized logistic process, a number of technologies and automated systems to handle a great number of containers and even greater volume of cargo. To answer these requirements, computation appears as important tool. The described scenary has been treated in academic literature as the Container Loading Problem (CLP), with some variants. It is necessary consider practical requirements, for example the stability of cargo or weight distribution. The last one is of vital importance since the position of the centre of gravity of cargo affects the stability during its transport. When desconsidered, it could result in damage to cargo or vehicle. During our research, we were specially interested in this requirement. But, in order compare the found solutions with other ones, we proposed a methodology to measures the weight distribution. So, to the described problem, specifically the Knapsack Loading Problem (3D-KLP), this work presents a methodology that not only maximizes the packed cargo volume but also optimizes the weight distribution, its great contribution. Mainly if we consider that the cargo to be packed is composed by items with different densities, which turns the problem more difficult. The present methodology is composed by two phases with distinct goals. The first phase is concerned with maximize the weight distribution combining a search algorithm, the backtracking, with heuristics that solve integer linear programming models. The second phase executes a Genetic Algorithm to maximize the weight distribution of previously packed cargo. We also present a justification for why genetic algorithm was used in our methodology. An additional application was made to solve cutting problems. This class of problems occurs in various industrial process, when it is necessary to cut different types of material as glass, wood or parper, with a minimum of waste. We use a well-known benchmark test to compare our results with other approaches. This work also presents a case study of our implementation using some real data in a factory of stoves and refrigerators in Brazil. It shown promising results in reduced time. Keywords: Container Loading Problem, Knapsack Loading Problem, Weight Distribution, Integer Programming, Backtracking, Genetic Algorithms.
O transporte de carga tem representado um papel fundamental no desenvolvimento econômico no decorrer da história e a conteinerização trouxe grandes vantagens. Seu advento reduziu os custos de transporte bem como o tempo de carga. Portanto, aumentou a eficiência do trabalho em portos e reduziu o tempo necessário para operações com carga para horas, ao invés de semanas como anteriormente. Contudo, o bom uso dos contêineres involve novos e especializados processos logísticos, uma grande quantidade de tecnologias além de sistemas automatizados para manipular uma elevada quantidade de contêineres e ainda maior volume de carga. Para atender a estes requisitos, computação aparece como uma importante ferramenta. O cenário descrito tem sido tratado na literatura acadêmica como o Problema de Carregamento de Contêiner (CLP, do inglês Container Loading Problem), com algumas variantes. é também necessário considerar requisitos práticos como, por exemplo, a estabilidade da carga ou distribuição do peso. Este último de vital importância uma vez que o centro de gravidade da carga afeta a estabilidade durante seu transporte. Se descosiderado, pode-se danificar tanto a carga como o veículo. Durante nossa pesquisa, nós estivemos especialmente interessados neste requisito. E a fim de comparar a qualidade dos resultados obtidos, propusemos uma maneira de mensurar a distribuição do peso. Portanto, dado o problema descrito, especificamente o 3D Knapsack Loading Problem, este trabalho apresenta um algoritmo que não apenas maximiza o volume total carregado mas também otimiza a distribuição do peso da carga, sua grande contribuição. Principalmente se considerarmos que a carga é composta de itens com diferentes valores de densidade, o que torna o problema ainda mais difícil. A metodologia consiste em duas fases com objetivos diferentes. A primeira fase ocupa-se em maximizar o volume carregado por combinar um algoritmo de busca, o backtracking, com heurísticas que resolvem modelos de programação linear inteira. A segunda fase executa um algoritmo genético para maximizar a distribuição do peso da carga previamente colocada. Apresentamos também uma justificativa do porque algoritmo genéticos foram usados em nossa metodologia. Uma aplicação adicional foi feita para resolver problemas de corte. Esta classe de problemas ocorre em vários processos industriais, quando é necessário cortar diferentes tipos de materiais, como vidro, madeira ou papel, com um mínimo de desperdício. A fim de comparação, usamos bibliotecas de teste bem conhecidas na literatura e um estudo de caso usando informações reais de uma fábrica de fogões e geladeiras no Brasil. São apresentados resultados promissores alcançados em tempo reduzido. Palavras-chave: Problema de Carregamento de Contêiner, Knapsack Loading Problem, Distribuição do Peso, Programação Linear Inteira, Backtracking, Algoritmos Genéticos.
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Remi-Omosowon, Ayodeji. "Applying computational intelligence to a real-world container loading problem in a warehouse environment." Thesis, Nottingham Trent University, 2017. http://irep.ntu.ac.uk/id/eprint/33547/.

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One of the problems presented in the day-to-day running of a warehouse is that of optimally selecting and loading groups of heavy rectangular palletised goods into larger rectangular containers while satisfying a number of practical constraints. The research presented in this thesis was commissioned by the logistics department in NSK Europe Ltd, for the purpose of providing feasible solutions to this problem. The problem is a version of the Container Loading Problem in the literature, and it is an active research area with many practical applications in industry. Most of the advances made in this area focus more on the optimisation of container utility i.e. volume or weight capacity, with very few focusing on the practical feasibility of the loading layout or pattern produced. Much of the work done also addresses only a few practical constraints at a time, leaving out a number of constraints that are of importance in real-world container loading. As this problem is well known to be a combinatorial NPhard problem, the exact mathematical methods that exist for solving it are computationally feasible for only problem instances with small sizes. For these reasons, this thesis investigates the use of computational intelligence techniques for solving and providing near-optimum solutions to this problem while simultaneously satisfying a number of practical constraints that must be considered for the solutions provided to be feasible. In proposing a solution to this problem and dealing with all the constraints considered, an algorithmic framework that decomposes the CLPs into sub-problems is presented. Each subproblem is solved using an appropriate algorithm, and a combination of constraints particular to each problem is satisfied. The resulting hybrid algorithm solves the entire problem as a whole and satisfies all the considered constraints. In order to identify and select feasible container layouts that are practical and easy to load, a measure of disorder, based on the concept of entropy in physics and information theory, is derived. Finally, a novel method of directing a Monte-Carlo tree search process using the derived entropy measure is employed, to generate loading layouts that are comparable to those produced by expert human loaders. In summary, this thesis presents a new approach for dealing with real-world container loading in a warehouse environment, particularly in instances where layout complexity is of major importance; such as the loading of heavy palletised goods using forklift trucks. The approach can be used to deal with a number of relevant practical constraints that need to be satisfied simultaneously, including those encountered when the heavy goods are arranged and physically packed into a container using forklift trucks.
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Heinze, Anja. "Optimisation of BMW Group Standardised Load Units via the Pallet Loading Problem." Thesis, Linköping University, Department of Management and Economics, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-5804.

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The BMW Group uses load units for the transportation of assembly parts from the suppliers to the plants and for the internal material flow. This thesis analyses the advantageousness of introducing a load unit with a new size. There are three reasons why the current choice of containers is not sufficient. Firstly, there is a certain range of assembly parts that does not fit very well into the existing standard load units. Secondly, the average measurements of the parts have grown in the last years and thirdly, several of the existing containers leave unused space in the transportation vehicles.

For this the relevant costs and other, more qualitative aspects like the placing at the assembly line are considered. A container size is identified that offers a significant savings potential. For this potential the handling and transportation costs are identified as the relevant leverages. These costs are found to depend mainly on the utilisation degree of the load units.

To calculate the different utilisation degrees, a packing-algorithm in form of a four-block heuristic is applied and its results are extrapolated on the basis of existing BMW packing information. Thus, several assembly parts are identified that fit better into the suggested load unit than in the existing ones. These results are assessed using BMW’s expense ratios for handling and transportation. 80 parts are determined for which the migration to the new size would result in savings of more than 5,000 EUR for each per year in Dingolfing. Together, these parts offer a savings potential of about 0.9 million Euro.

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Vendramini, Eliane [UNESP]. "Otimização do problema de carregamento de container usando uma metaheurística eficiente." Universidade Estadual Paulista (UNESP), 2007. http://hdl.handle.net/11449/87262.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
No âmbito de pesquisa operacional o problema de carregamento de container é conhecido por determinar uma configuração de carga que procure otimizar o que será carregado em um container, levando em consideração o máximo de volume ocupado pela carga. Este problema tem diversas variantes para casos específicos. Existem casos onde a carga é homogênea ou heterogênea, onde a carga pode ser rotacionada em todas as suas dimensões, onde um lucro é associado a cada caixa carregada, entre outras variantes, onde a questão não é a carga e sim o container. A classificação do problema está diretamente ligada a suas restrições. O estudo de carregamento de container aqui no Brasil começou ser realizado com mais ênfase há pouco tempo, por ter despertado interesses financeiros em empresas públicas e privadas, já que o transporte utilizando containers é oneroso e cobrado por container alugado e não pela quantidade de itens que serão carregados. Por isso a vantagem de aproveitar o volume do container ao máximo. Na literatura podem ser encontradas diversas propostas de solução para cada variante do problema, sendo estas propostas determinísticas ou utilizando heurísticas e metaheurísticas. O estudo realizado para a apresentação desta dissertação descreve de maneira ampla as heurísticas que estão sendo empregadas na resolução do problema estudado, bem como propõe uma nova heurística especializada. O trabalho aqui apresentado traz ainda uma metaheurística especializada, o algoritmo genético Chu-Beasley. Portanto, foram desenvolvidos dois algoritmos: um heurístico e um metaheurístico. Estes algoritmos simularam o carregamento de um container com caixas retangulares e de diferentes tamanhos, sendo no final comparados os...
In the ambit of the operational research the container loading problem is known by optimized the load that it will be carried in a container, taking in consideration the maximum of volume occupied by the load. This problem has several variants for specific cases. Cases exist where the load is homogeneous or heterogeneous, where the load can be rotated in whole its dimensions, where a profit associated to each loaded box exists, among other variants, where the subject is not the load, but the container. The classification of the problem is directly tied up to its restrictions. The study of the container loading problem here in Brazil it began to be accomplished with more emphasis at little time, for having wakened up financial interests in public and private companies, since the transport using containers is onerous and collected by rented container and not for the amount of items that you will be loaded. That the advantage of taking advantage of the volume of the container to the maximum. In the literature it can be found several proposed of solution for each variant of the problem. Being these proposed deterministics or using heuristics and metaheuristics. The study accomplished for the presentation of this dissertation brings in a wide way the heuristics that you are being used in the resolution of the problem, as well as it proposes a new heuristic specialized for the resolution of the container loading problem. The work here presented he still brings a metaheuristic specialized for the resolution of the problem, the Chu-Beasley genetic algorithm. Therefore, two algorithms were developed: a heuristic and a metaheuristic. These algorithms simulated the shipment of a container with rectangular boxes and of different sizes, being in the compared end... (Complete abstract, click electronic access below)
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Lima, Bruna Gonçalves de [UNESP]. "Meta-heurística age-e aplicada a problemas de carregamento de contêiners." Universidade Estadual Paulista (UNESP), 2017. http://hdl.handle.net/11449/152072.

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Neste trabalho apresenta-se uma nova meta-heurística, o Algoritmo Genético Evolucionário Especializado (AGE-E) para resolver uma das categorias dos Problemas de Carregamento de Contêiners, objeto de estudo que pertence à otimização, na Pesquisa Operacional. Considera-se a existência de múltiplos contêiners de iguais dimensões que permitem o carregamento completo da carga disponível em um contexto de transporte industrial. Esta carga é composta por caixas de sortimento fortemente hete-rogêneo e que permite a rotação em qualquer dasseis possibilidades, tornando o problema ainda mais complexo, e, porisso,menos estudado na literatura. Uma revisão bibliográfica é também apresentada, contendo uma visão geral das classificações do problema e, em particular, um estudo aprofundado sobre algoritmos genéticos. A implementação do AGE-E foi realizada, e os resultados computacionais foram comparados com as melhores soluções já apresentadas na literatura, demonstrando o potencial do AGE-E para estudosfuturos.
This work presents a new meta-heuristic, the Specialized Evolutionary Genetic Algorithm (AGE-E), which solves one of the categories of Container Loading Problems, object of study that belongs to Optimization, within the Operational Research. It’s considered the existence of multiple containers ofthe equal dimensionsthat promote the full loading of the availablecargoinindustrial transportation context. Thisload is composed ofstrongly heterogeneous assortment to the boxes, and allows rotation in any of the six possibilities, making the problem even more complex, and therefore less studied in the literature. A bibliographic review is also presented, containing an overview of the classifications of the problem and, in particular, an deepened study on genetic algorithms. The implementation of AGE-E was performed, and the computational results were compared with the best solutions already determined by the bibliography, demonstrating the potentialofAGE-E for future studies.
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Lima, Bruna Gonçalves de. "Meta-heurística age-e aplicada a problemas de carregamento de contêiners /." Ilha Solteira, 2017. http://hdl.handle.net/11449/152072.

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Orientador: Rubén Augusto Romero Lázaro
Resumo: Neste trabalho apresenta-se uma nova meta-heurística, o Algoritmo Genético Evolucionário Especializado (AGE-E) para resolver uma das categorias dos Problemas de Carregamento de Contêiners, objeto de estudo que pertence à otimização, na Pesquisa Operacional. Considera-se a existência de múltiplos contêiners de iguais dimensões que permitem o carregamento completo da carga disponível em um contexto de transporte industrial. Esta carga é composta por caixas de sortimento fortemente hete-rogêneo e que permite a rotação em qualquer dasseis possibilidades, tornando o problema ainda mais complexo, e, porisso,menos estudado na literatura. Uma revisão bibliográfica é também apresentada, contendo uma visão geral das classificações do problema e, em particular, um estudo aprofundado sobre algoritmos genéticos. A implementação do AGE-E foi realizada, e os resultados computacionais foram comparados com as melhores soluções já apresentadas na literatura, demonstrando o potencial do AGE-E para estudosfuturos.
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Book chapters on the topic "Container loading problem"

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Scheithauer, Guntram. "Algorithms for the Container Loading Problem." In Operations Research Proceedings 1991, 445–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-46773-8_112.

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Scheithauer, Guntram. "LP-bounds for the Container and Multi-Container Loading Problem." In Operations Research Proceedings, 123–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-60744-8_23.

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Tian, Tian, Andrew Lim, and Wenbin Zhu. "A Heuristic to the Multiple Container Loading Problem with Preference." In Contemporary Challenges and Solutions in Applied Artificial Intelligence, 219–24. Heidelberg: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00651-2_30.

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Che, Chan Hou, Weili Huang, Andrew Lim, and Wenbin Zhu. "A Heuristic for the Multiple Container Loading Cost Minimization Problem." In Lecture Notes in Computer Science, 276–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21827-9_28.

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Wu, Yuen-Ting, and Yu-Liang Wu. "A Less Flexibility First Based Algorithm for the Container Loading Problem." In Operations Research Proceedings 2004, 368–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/3-540-27679-3_46.

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González, Yanira, Gara Miranda, and Coromoto León. "A Multi-level Filling Heuristic for the Multi-objective Container Loading Problem." In Advances in Intelligent Systems and Computing, 11–20. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-01854-6_2.

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Junqueira, Leonardo, Reinaldo Morabito, Denise Sato Yamashita, and Horacio Hideki Yanasse. "Optimization Models for the Three-Dimensional Container Loading Problem with Practical Constraints." In Springer Optimization and Its Applications, 271–93. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-4469-5_12.

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Ferreira, Ana Rita, António G. Ramos, and Elsa Silva. "Analysis of the Impact of Physical Internet on the Container Loading Problem." In Lecture Notes in Computer Science, 549–61. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87672-2_36.

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Gliozzi, Stefano, Alessandro Castellazzo, and Giorgio Fasano. "A Container Loading Problem MILP-Based Heuristics Solved by CPLEX: An Experimental Analysis." In Optimized Packings with Applications, 157–73. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18899-7_7.

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Cardoso, Rodrigo Nogueira, Marco Vinícius Muniz Ferreira, Alexandre Rodrigues de Sousa, and José Jean-Paul Zanlucchi Souza Tavares. "A Genetic Algorithm Approach to the Automated System for Solving the Container Loading Problem." In Communications in Computer and Information Science, 267–80. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47247-8_16.

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Conference papers on the topic "Container loading problem"

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Lim, Andrew, and Xingwen Zhang. "The container loading problem." In the 2005 ACM symposium. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1066677.1066888.

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Erdem, Huseyin Askin. "Solving container loading problem with genetic algorithm." In 2014 IEEE 15th International Symposium on Computational Intelligence and Informatics (CINTI). IEEE, 2014. http://dx.doi.org/10.1109/cinti.2014.7028707.

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Wang, Yan, Hailiang Li, Zhibin Lei, Danpeng Ma, and Yang Fang. "Progressively-Refined Tree Search for Container Loading Problem." In 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). IEEE, 2019. http://dx.doi.org/10.1109/hpcc/smartcity/dss.2019.00353.

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Erkalkan, Ercan, Vedat TOPUZ, and Ali BULDU. "Solving Container Loading Problem with Differential Evolution Algorithm." In 2020 Innovations in Intelligent Systems and Applications Conference (ASYU). IEEE, 2020. http://dx.doi.org/10.1109/asyu50717.2020.9259863.

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Can, Okan, and Ozgur Koray Sahingoz. "Solving container loading problem with simulated annealing algorithm." In 2014 IEEE 15th International Symposium on Computational Intelligence and Informatics (CINTI). IEEE, 2014. http://dx.doi.org/10.1109/cinti.2014.7028705.

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de Armas, Jesica, Yanira Gonzalez, Gara Miranda, and Coromoto Leon. "Parallelization of the multi-objective container loading problem." In 2012 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2012. http://dx.doi.org/10.1109/cec.2012.6256123.

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González, Yanira, Coromoto León, Gara Miranda, and Javier Villamonte. "Graphical User Interface for the Container Loading Problem." In the XV International Conference. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2662253.2662322.

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Ho, Ziao-Fung, Lai-Soon Lee, Zanariah Abdul Majid, and Hsin-Vonn Seow. "An improved GRMOD heuristic for container loading problem." In INTERNATIONAL CONFERENCE ON MATHEMATICAL SCIENCES AND STATISTICS 2013 (ICMSS2013): Proceedings of the International Conference on Mathematical Sciences and Statistics 2013. AIP, 2013. http://dx.doi.org/10.1063/1.4823952.

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Lv, G. M., and G. Shen. "Container Loading Problem Based on Improved Genetic Algorithm." In First International Conference on Transportation Engineering. Reston, VA: American Society of Civil Engineers, 2007. http://dx.doi.org/10.1061/40932(246)222.

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Xue, Jun, and Qing Li. "Scatter Search Algorrithm to Multiple Container Loading Problem." In First International Conference on Transportation Engineering. Reston, VA: American Society of Civil Engineers, 2007. http://dx.doi.org/10.1061/40932(246)620.

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