COPERSUCAR Ltda (the acronym for the Sugarcane and Ethanol Producers' Cooperative in Sa˜o Paulo state) is a Brazilian cooperative of sugarcane producers and the largest sugar and ethanol manufacturer in Brazil, producing 4.4 million metric tons of sugar and 2.7 billion liters of ethanol. The cooperative is composed of 34 sugar mills with centralized sales and marketing. This organization establishes the amount of each product that will be manufactured in each mill to reduce total transportation and storage costs and, consequently, increase overall gain. Critical aspects of this problem are seasonal production and, therefore, the need to store final products to meet demand during the off-season period. This study focuses on the application of a multi-period linear programming model that provides optimal assignment of production, transportation, and storage of final products subject to manufacturing and flow capacity constraints. The expected annual benefits of implementing the proposed solution are 3.3 million dollars. In addition, a sensitivity analysis was carried out to investigate the possibility of increasing the capacity of the installed mills.Founded in July 1959, COPERSUCAR is composed of 34 sugar mills, 31 of which are concentrated in the state of Sa˜o Paulo, as shown in Fig. 1. With centralized management of sales and marketing, this group serves clients throughout Brazil. This cooperative is the largest sugarcane manufacturer in Brazil, with a production of 4.4 million metric tons of sugar and 2.7 billion liters of ethanol (data for the 1999/2000 crop). It is also the market leader, accounting for 26% of the sugar market and 23% of the ethanol market in the central and southern regions of Brazil.This study focuses on the application of a linear programming (LP) model that provides the optimal assignment of production, transportation, and warehousing for each period within the logistics system managed by COPERSUCAR. Critical aspects of this problem are seasonal production and the resulting need to store final products to meet demand during the off-season. Thus, production planning involves decisions such as distribution of the production mix between several plants according to their individual capacity, the need for totally external storage, and management of inventory levels for each plant.Numerous mathematical programming models applied to production and distribution problems can be found in the literature. Gehring et al. (1991) used LP in the integrated planning of production and distribution of cement. Gutierrez (1996) developed a multi-period, multiproduct LP model to optimize production, inventory placement (raw materials and final products), and distribution of a company that deals with agricultural input with high seasonal demand. Schuster and Allen (1998) approached the problem of aggregate planning for a manufacturer of fruit-derived products, minimizing transportation, manufacturing, and storage costs. Hindi et al. (1998) presented an application of a multi-product transshipment model for the ...
Abstract. This paper addresses the single machine scheduling problem with a common due date aiming to minimize earliness and tardiness penalties. Due to its complexity, most of the previous studies in the literature deal with this problem using heuristics and metaheuristics approaches. With the intention of contributing to the study of this problem, a branch-and-bound algorithm is proposed. Lower bounds and pruning rules that exploit properties of the problem are introduced. The proposed approach is examined through a computational comparative study with 280 problems involving different due date scenarios. In addition, the values of optimal solutions for small problems from a known benchmark are provided.Mathematical subject classification: 90C11, 62P30, 90B35.
Aplicação do método branch-and-bound na programação de tarefas em uma única máquina com data de entrega comum sob penalidades de adiantamento e atraso / M.S. Kawamura.-São Paulo, 2006. 62 p. Dissertação (Mestrado)
This paper addresses an integrated lot-sizing and scheduling problem in the industry of consumer goods for personal care, a very competitive market in which the good customer service level and the cost management show up in the competition for the clients. In this research, a complex operational environment composed of unrelated parallel machines with limited production capacity and sequence-dependent setup times and costs is studied. There is also a limited finished-goods storage capacity, a characteristic not found in the literature. Backordering is allowed but it is extremely undesirable. The problem is described through a mixed integer linear programming formulation. Since the problem is NP-hard, relax-and-fix heuristics with hybrid partitioning strategies are investigated. Computational experiments with randomly generated and also with real-world instances are presented. The results show the efficacy and efficiency of the proposed approaches. Compared to current solutions used by the company, the best proposed strategies yield results with substantially lower costs, primarily from the reduction in inventory levels and better allocation of production batches on the machines.
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