997 resultados para STOCK PROBLEMS
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We investigate several two-dimensional guillotine cutting stock problems and their variants in which orthogonal rotations are allowed. We first present two dynamic programming based algorithms for the Rectangular Knapsack (RK) problem and its variants in which the patterns must be staged. The first algorithm solves the recurrence formula proposed by Beasley; the second algorithm - for staged patterns - also uses a recurrence formula. We show that if the items are not so small compared to the dimensions of the bin, then these algorithms require polynomial time. Using these algorithms we solved all instances of the RK problem found at the OR-LIBRARY, including one for which no optimal solution was known. We also consider the Two-dimensional Cutting Stock problem. We present a column generation based algorithm for this problem that uses the first algorithm above mentioned to generate the columns. We propose two strategies to tackle the residual instances. We also investigate a variant of this problem where the bins have different sizes. At last, we study the Two-dimensional Strip Packing problem. We also present a column generation based algorithm for this problem that uses the second algorithm above mentioned where staged patterns are imposed. In this case we solve instances for two-, three- and four-staged patterns. We report on some computational experiments with the various algorithms we propose in this paper. The results indicate that these algorithms seem to be suitable for solving real-world instances. We give a detailed description (a pseudo-code) of all the algorithms presented here, so that the reader may easily implement these algorithms. (c) 2007 Elsevier B.V. All rights reserved.
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The following work is a case study of overstock and stock-out problems at Volkswagen Autoeuropa (VWAE). It introduces the supply chain of Autoeuropa and specializes then on failures connected to inventory problems. Having a successful supply chain is important in a world where products become more and more similar as it can give to companies an edge over their competitors. The case shows three practices that VWAE uses to prevent and to overcome stock problems. Information was gathered by doing interviews with different managers, by analyzing the company’s key processes and by literature research related to the topics of supply chain management and flexibility in the supply chain. Three practices were further investigated: the use of alternative parts, support of the supplier and a rating system of suppliers. In the question section of this work the importance of flexibility and Supplier Relationship Management (SRM) when connected to supply chain management are explained. The described different practices are numerically analyzed and it is concluded that each practice brings both cost savings and the possibility of achieving target numbers to the company, showing the company’s flexibility to react to supply chain disturbances. Because of confidentiality reasons, persons in the case are fictionalized and numbers are wherever possible equalized to 100 in order to display true proportions.
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This paper addresses the one-dimensional cutting stock problem when demand is a random variable. The problem is formulated as a two-stage stochastic nonlinear program with recourse. The first stage decision variables are the number of objects to be cut according to a cutting pattern. The second stage decision variables are the number of holding or backordering items due to the decisions made in the first stage. The problem`s objective is to minimize the total expected cost incurred in both stages, due to waste and holding or backordering penalties. A Simplex-based method with column generation is proposed for solving a linear relaxation of the resulting optimization problem. The proposed method is evaluated by using two well-known measures of uncertainty effects in stochastic programming: the value of stochastic solution-VSS-and the expected value of perfect information-EVPI. The optimal two-stage solution is shown to be more effective than the alternative wait-and-see and expected value approaches, even under small variations in the parameters of the problem.
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Industrial production processes involving both lot-sizing and cutting stock problems are common in many industrial settings. However, they are usually treated in a separate way, which could lead to costly production plans. In this paper, a coupled mathematical model is formulated and a heuristic method based on Lagrangian relaxation is proposed. Computational results prove its effectiveness. (C) 2009 Elsevier B.V. All rights reserved.
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An important production programming problem arises in paper industries coupling multiple machine scheduling with cutting stocks. Concerning machine scheduling: how can the production of the quantity of large rolls of paper of different types be determined. These rolls are cut to meet demand of items. Scheduling that minimizes setups and production costs may produce rolls which may increase waste in the cutting process. On the other hand, the best number of rolls in the point of view of minimizing waste may lead to high setup costs. In this paper, coupled modeling and heuristic methods are proposed. Computational experiments are presented.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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We consider a one-dimensional cutting stock problem in which the material not used in the cutting patterns, if large enough, is kept for use in the future. Moreover, it is assumed that leftovers should not remain in stock for a long time, hence, such leftovers have priority-in-use compared to standard objects (objects bought by the industry) in stock. A heuristic procedure is proposed for this problem, and its performance is analyzed by solving randomly generated dynamic instances where successive problems are solved in a time horizon. For each period, new demands arise and a new problem is solved on the basis of the information about the stock of the previous periods (remaining standard objects in the stock) and usable leftovers generated during those previous periods. The computational experiments show that the solutions presented by the proposed heuristic are better than the solutions obtained by other heuristics from the literature. © 2012 The Authors. International Transactions in Operational Research © 2012 International Federation of Operational Research Societies.
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O presente trabalho visa denotar a importância de ferramentas e técnicas utilizadas como apoio à tomada de decisão. Foi proposto um problema de corte cujo objectivo primordial procura minimizar o desperdício gerado resultante do processo de obtenção de um produto, utilizando um caso representativo de um produto em chapa, fabricado por uma empresa que conta três décadas de laboração contínua, proposeram-se e realizaram-se estudos no sentido de solucionar recursos causadores de desperdício. Neste trabalho aplicou-se um problema de corte bi-dimensional a uma indústria que recorre ao fabrico de produtos em chapa, por forma a minimizar o desperdício relativo ao processo utilizado. Propôs-se quatro alternativas à solução actual realizada na empresa, que passa pela disposição e combinação de vários tipos de cortes-padrão que podem ser executados nas diferentes dimensões de matéria-prima disponibilizada. Estas alternativas têm como vantagem apresentar reduções que se traduzam significativas para os custos implícitos à realização do processo produtivo. Os estudos computacionais praticados mostraram que as soluções propostas como alternativa obtiveram melhores resultados que os obtidos pela empresa, excepto num caso.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Pós-graduação em Matemática - IBILCE
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In this paper a mathematical model that combines lot-sizing and cutting-stock problems applied to the furniture industry is presented. The model considers the usual decisions of the lot sizing problems, as well as operational decisions related to the cutting machine programming. Two sets of a priori generated cutting patterns are used, industry cutting patterns and a class of n-group cutting patterns. A strategy to improve the utilization of the cutting machine is also tested. An optimization package was used to solve the model and the computational results, using real data from a furniture factory, show that a small subset of n-group cutting patterns provides good results and that the cutting machine utilization can be improved by the proposed strategy.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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In this study, a dynamic programming approach to deal with the unconstrained two-dimensional non-guillotine cutting problem is presented. The method extends the recently introduced recursive partitioning approach for the manufacturer's pallet loading problem. The approach involves two phases and uses bounds based on unconstrained two-staged and non-staged guillotine cutting. The method is able to find the optimal cutting pattern of a large number of pro blem instances of moderate sizes known in the literature and a counterexample for which the approach fails to find known optimal solutions was not found. For the instances that the required computer runtime is excessive, the approach is combined with simple heuristics to reduce its running time. Detailed numerical experiments show the reliability of the method. Journal of the Operational Research Society (2012) 63, 183-200. doi: 10.1057/jors.2011.6 Published online 17 August 2011
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Contribution from Bureau of Animal Industry.