O problema de corte de estoque unidimensional multiperíodo

The Multiperiod Cutting Stock Problem arises embedded in the production planning and programming in many industries which have a cutting process as an important stage. Ordered items have different due date over a finite planning horizon. A large scale integer linear optimization model is proposed. The model makes possible to anticipate or not the production of items. Unused objects in inventory in a period become available to the next period, added to new inventory, which are acquired or produced by the own company. The mathematical model's objective considers the waste in the cutting process, and costs for holding objects and final items. The simplex method with column generation was specialized to solve the linear relaxation. Some preliminary computational experiments showed that the multiperiod model could obtain effective gains when compared with the lot-for-lot solution, which is typically used in practice. However, in real world problems, the fractional solution is useless. So, additionally, two rounding procedures are developed to determine integer solutions for multiperiod cutting stock problems. Such procedures are based on a rolling horizon scheme, which roughly means, find an integer solution only for the first period, since this is the solution to be, in fact, carried out. Finally, we conclude that the proposed model for multiperiod cutting stock problems allows flexibility on analyzing a solution to be put in practice. The multiperiod cutting problem can be a tool that provides the decision maker a wide view of the problem and it may help him/her on making decisions.O problema de corte de estoque multiperíodo surge imerso no planejamento e programação da produção em empresas que têm um estágio de produção caracterizado pelo corte de peças. As demandas dos itens ocorrem em períodos diversos de um horizonte de planejamento finito, sendo possível antecipar ou não a produção de itens. Os objetos não utilizados em um período ficam disponíveis no próximo, juntamente com possíveis novos objetos adquiridos ou produzidos pela própria empresa. Um modelo de otimização linear inteira de grande porte é proposto, cujo objetivo pondera as perdas nos cortes, os custos de estocagem de objetos e itens. O método simplex com geração de colunas foi especializado para resolver a relaxação linear. Experiências computacionais preliminares mostram que ganhos efetivos podem ser obtidos, quando comparado com a solução lote-por-lote, tipicamente utilizada na prática. No entanto, em problemas práticos, uma solução fracionária não é aplicável. Então, foram desenvolvidas duas abordagens para o arredondamento da solução para o problema de corte de estoque multiperíodo. Tais procedimentos são baseados em horizonte rolante, que basicamente, consiste em tentar encontrar uma solução inteira apenas para o primeiro período, já que esta será uma solução implementada na prática; para os demais períodos pode haver mudança na demanda, por exemplo, a chegada de novos pedidos ou o cancelamento de pedidos. Finalmente, concluímos que o modelo proposto para o problema de corte de estoque multiperíodo permite flexibilidade na análise da solução a ser posta em prática. O modelo multiperíodo pode ser uma ferramenta que fornece ao tomador de decisões uma ampla visão do problema e pode auxiliá-lo na tomada de decisão.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Universidade Federal de São Paulo (UNIFESP) Departamento de Ciência e TecnologiaUniversidade de São Paulo Inst. de Ciências Matemáticas e de ComputaçãoUNIFESP, Depto. de Ciência e TecnologiaSciEL

A genetic algorithm for the one-dimensional cutting stock problem with setups

This paper investigates the one-dimensional cutting stock problem considering two conflicting objective functions: minimization of both the number of objects and the number of different cutting patterns used. A new heuristic method based on the concepts of genetic algorithms is proposed to solve the problem. This heuristic is empirically analyzed by solving randomly generated instances and also practical instances from a chemical-fiber company. The computational results show that the method is efficient and obtains positive results when compared to other methods from the literature. © 2014 Brazilian Operations Research Society

"Algumas extensões do problema de corte de estoque"

A dissertação apresenta o problema de corte de estoque, que é um problema de otimização inteiro, difícil de ser resolvido computacionalmente. Resolvemos o problema relaxando a condição de integralidade pelo método simplex com geração de colunas, mas esta solução não é viável na prática. Estudamos várias heurísticas para a obtenção da solução inteira do problema

The multiperiod cutting stock problem

Problemas de corte de estoque consistem em arranjar peças menores, em tamanhos e quantidades especificados, dentro de peças maiores. Tais problemas têm sido investigados intensamente nas últimas décadas, acrescidos de novas características e novos métodos de solução. Nesta tese abordamos o problema de corte de estoque multiperíodo que surge imerso no planejamento e programação da produção em empresas que têm um estágio de produção caracterizado pelo corte de peças. As demandas dos itens ocorrem em períodos diversos de um horizonte de planejamento finito, sendo possível antecipar ou não a produção de itens. Os objetos disponíveis em estoque não utilizados em um período ficam disponíveis no próximo período, juntamente com novos objetos adquiridos ou produzidos pela própria empresa. Um modelo de otimização linear inteira de grande porte é proposto, cujo objetivo pondera o custo das perdas nos cortes, os custos de estocagem de objetos e itens. O método simplex com geração de colunas foi especializado para resolver a relaxação linear do modelo proposto. Foram realizados experimentos computacionais com problemas de corte de estoque unidimensional e bidimensional. Tais experimentos mostram que ganhos efetivos podem ser obtidos usando-se o modelo de corte de estoque multiperíodo, quando comparado com a solução lote-por-lote, tipicamente utilizada na prática. Porém, na prática, a solução relaxada é de pouca, ou nenhuma, utilidade. Assim, nesta tese, desenvolvemos dois procedimentos de arredondamento da solução do problema multiperíodo, baseado em horizonte rolante, ou seja, determinamos uma solução inteira factível apenas para o primeiro período, a qual será, de fato, implementada. Enfim, concluímos que o modelo para o problema de corte de estoque multiperíodo permite flexibilidade na análise de uma solução a ser implementada e, portanto, é uma ferramenta que permite ao gerente de produção uma visão global do problema para auxiliá-lo na tomada de decisõesCutting stock problems consist of cutting a set of available stock objects in order to produce smaller ordered items. Such problems have been intensively researched over the last decades, together with additional characteristics and new methods for solving them. In this thesis, we address the multiperiod cutting stock problem, which arises in the production planning and programming in many industries that have a cutting process as an important stage. Ordered items have different due date over a finite planning horizon. An integer linear optimization model of large scale is proposed. The model makes possible to anticipate or not the production of items. Unused objects in inventory in a period become available to the next period, added to new inventory, which are acquired or produced by the own company. The mathematical model\'s objective is to minimize the cost of waste in the cutting process and costs for holding objects and fInal items. The simplex method with column generation was specialized to solve its linear relaxation. Computational experiments were carried out to solve one-dimensional and two-dimensional cutting stock problems. Such experiments showed that the multiperiod model could obtain effective gains when compared with the lot-for-lot solution, which is typically used in practice. However, in practical problems, the fractional solution is useless. So, in this thesis, two rounding procedures are developed to determine integer solutions for multiperiod cutting stock problems. Such procedures are based on a rolling horizon scheme, which roughly means, find an integer solution only for the first period, since this is the solution to be, in fact, carried out. Finally, we conclude that the proposed model for multiperiod cutting stock problems allows flexibility on analyzing a solution to be put in practice. The multiperiod cutting problem can be a tool that provides the decision maker a wide view of the problem and it may help him/her on making decision

Mathematical models for the cutting stock with limited open stacks problem

This research is focused on solving the Cutting Stock with Limited Open Stacks Problem (CS-LOSP). The CS-LOSP is an optimization problem which consists of the classical Cutting Stock Problem (CSP) paired with the additional constraint that the maximum number of open stacks from the sequencing of the cutting patterns obtained from the CSP solution is equal or lower than a preset limit. Despite being a problem with great practical importance, the literature lacks models for this problem, and only one-dimensional problems are addressed. In this paper, we propose two integer linear programming formulations for the CS-LOSP that are valid for solving instances of the CSP of any dimension. In order to eliminate symmetrical solutions to the problem, the proposed formulations sequence sets of cutting patterns instead of sequencing the cutting patterns individually, thus, the search space for solutions is reduced. A set of randomly generated instances for the two-dimensional problem is used to perform computational experiments in order to validate the proposed mathematical formulations

Mathematical models and a heuristic method for the multiperiod one-dimensional cutting stock problem

CAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIORCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOThe multiperiod cutting stock problem arises in the production planning and programming of many industries that have the cutting process as an important stage. Ordered items are required in different periods of a finite planning horizon. It is possible to bring forward or not the production of items. Unused inventory in a certain period becomes available for the next period, all together with new inventory which may come to be acquired in the market. Based on mixed integer optimization models from the literature, extensions are proposed to deal with the multiperiod case and a residual heuristic is used. Computational experiments showed that effective gains can be obtained when comparing multiperiod models with the lot for lot solution, which is typically used in practice. Most of the instances are solved satisfactorily with a high performance optimization package and the heuristic method is used for solving the hard instances. © 2016 Springer Science+Business Media New YorkThe multiperiod cutting stock problem arises in the production planning and programming of many industries that have the cutting process as an important stage. Ordered items are required in different periods of a finite planning horizon. It is possible to bring forward or not the production of items. Unused inventory in a certain period becomes available for the next period, all together with new inventory which may come to be acquired in the market. Based on mixed integer optimization models from the literature, extensions are proposed to deal with the multiperiod case and a residual heuristic is used. Computational experiments showed that effective gains can be obtained when comparing multiperiod models with the lot for lot solution, which is typically used in practice. Most of the instances are solved satisfactorily with a high performance optimization package and the heuristic method is used for solving the hard instances.2381-2497520CAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIORCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIORCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO2010/10133-02014/01203-52015/05193-

Heuristics for the one-dimensional cutting stock problem with limited multiple stock lengths

This paper deals with the classical one-dimensional integer cutting stock problem, which consists of cutting a set of available stock lengths in order to produce smaller ordered items. This process is carried out in order to optimize a given objective function (e.g., minimizing waste). Our study deals with a case in which there are several stock lengths available in limited quantities. Moreover, we have focused on problems of low demand. Some heuristic methods are proposed in order to obtain an integer solution and compared with others. The heuristic methods are empirically analyzed by solving a set of randomly generated instances and a set of instances from the literature. Concerning the latter. most of the optimal solutions of these instances are known, therefore it was possible to compare the solutions. The proposed methods presented very small objective function value gaps. (C) 2008 Elsevier Ltd. All rights reserved.Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

A coupling cutting stock-lot sizing problem in the paper industry

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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