ABSTRACT In this paper, the relevance of integrated planning concerning decisions of production and blending in a spinning industry is studied. The scenario regards a plant that produces several yarn packages over a planning horizon. Each yarn type is produced using a blend of several cotton bales that must contain attributes to ensure the quality of the produced yarns. Three approaches to managing production and blending are compared; the first deals with the solution to the production scheduling and blending problems in a single integrated model. The second approach hierarchically addresses these problems. The third procedure combines features from the integrated and hierarchical approaches. These approaches are applied to a real-world problem, and their respective performances are analyzed. The third approach proved to deal with lot sizing, scheduling and blending in the spinning industry more efficiently. Moreover, the results indicate the importance of coordinating production and blending decisions.

Neste trabalho estuda-se um problema de dimensionamento de lotes e distribuição que envolve além de custos de estoques, produção e preparação, custos de transportes para o armazém da empresa. Os custos logísticos estão associados aos contêineres necessários para empacotar os produtos produzidos. A empresa negocia um contrato de longo prazo onde um custo fixo por período é associado ao transporte dos itens, em contrapartida um limite de contêineres é disponibilizado com custo mais baixo que o custo padrão. Caso ocorra um aumento ocasional de demanda, novos contêineres podem ser utilizados, no entanto, seu custo é mais elevado. Um modelo matemático foi proposto na literatura e resolvido utilizando uma heurística Lagrangiana. No presente trabalho a resolução do problema por uma heurística Lagrangiana/surrogate é avaliada. Além disso, é considerada uma extensão do modelo da literatura adicionando restrições de capacidade e permitindo atraso no atendimento a demanda. Testes computacionais mostraram que a heurística Lagrangiana/surrogate é competitiva especialmente quando se têm restrições de capacidade apertada.

The aim of this work was to study a distribution and lot-sizing problem that considers costs with transportation to a company warehouse as well as, inventory, production and setup costs. The logistic costs are associated with necessary containers to pack produced items. The company negotiates a long-term contract in which a fixed cost per period is associated with the transportation of the items. On the other hand, a limited number of containers are available with a lower cost than the average cost. If an occasional demand increase occurs, other containers can be utilized; however, their costs are higher. A mathematical model was proposed in the literature and solved using the Lagrangian heuristic. Here, the use of the Lagrangian/surrogate heuristic to solve the problem is evaluated. Moreover, an extension of the literature model is considered adding capacity constraints and allowing backlogging. Computational tests show that Lagrangian/surrogate heuristics are competitive, especially when the capacity constraints are tight.

This paper addresses the capacitated lot sizing problem (CLSP) with a single stage composed of multiple plants, items and periods with setup carry-over among the periods. The CLSP is well studied and many heuristics have been proposed to solve it. Nevertheless, few researches explored the multi-plant capacitated lot sizing problem (MPCLSP), which means that few solution methods were proposed to solve it. Furthermore, to our knowledge, no study of the MPCLSP with setup carry-over was found in the literature. This paper presents a mathematical model and a GRASP (Greedy Randomized Adaptive Search Procedure) with path relinking to the MPCLSP with setup carry-over. This solution method is an extension and adaptation of a previously adopted methodology without the setup carry-over. Computational tests showed that the improvement of the setup carry-over is significant in terms of the solution value with a low increase in computational time.

O problema estudado neste trabalho visa minimizar o custo de energia elétrica necessário para a operação de bombas hidráulicas, que captam água de poços artesianos para os reservatórios distribuídos em bairros da cidade, de onde a população é atendida. Como o custo da energia elétrica varia ao longo do dia, se faz necessário um planejamento da operação das bombas e armazenamento de água no sistema. Um modelo de otimização linear inteira é proposto para o problema, considerando um custo de partida das bombas. Desconsiderando esse custo, as variáveis binárias do modelo são eliminadas e um segundo modelo de otimização linear é também analisado. Algumas instâncias geradas aleatoriamente são resolvidas e suas soluções analisadas, demonstrando que os modelos propostos oferecem suporte gerencial consistente para seu uso no problema real.

The aim of the problem studied in this paper is to minimize the electrical energy cost necessary to manage water distribution networks. We consider water distribution systems that are designed to deliver water from pump stations suitably distributed in a city, to the final water consumers. Since the cost of the electrical energy varies during the day, it is necessary to plan the operation of the pumps and water inventory in the system. An integer linear optimization model is proposed for the problem, when considering a fixed cost for the starting of the pumps. On the other hand, when we do not consider this cost, the binary variables are eliminated and the problem can be formulated as a linear optimization model. Some randomly generated instances are solved and corresponding solutions evaluated. The examples show that the proposed models offer consistent managerial support for their use in the real problem.