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Heuristic and exact methods for lot sizing problems


Due to fierce market competition, companies were driven to constantly improve and seek ways of producing high quality products at low operating costs. This situation led the industries to seek new technologies both for production and for the planning of their production process. In this context, production planning, which seeks to use company resources efficiently, has become an important tool in helping industries to achieve their goals. One of the most important tasks in production planning is to determine the lot size of the products that are made over a certain planning horizon so that production demand is met. This problem is known in literature as the lot sizing problem. In this project we will basically approach two lot sizing problems inspired on real situations. For these problems, we will consider a finite planning horizon, which is then split into periods. For each period, the demand of the items and the quantity of resource available are known. Our goal is to minimize the total production cost that is composed of inventory costs and setup costs. The available production resources are limited and setup times are necessary. This problem is a combinatorial optimization problem difficult to solve, which justifies the use of heuristics to solve it. Therefore, our goal is to propose heuristics and /or the meta-heuristics for solving studied problems. In addition, we will study new strategies for integer optimization and we will try to develop exact methods through which we can solve the problems that are at hand. We aim to assess the effectiveness of these strategies for solving these specific problems. In this context, we seek to develop new lines of research related to the topic. The proposed work should bring important contributions to our research area and should contribute to the enrichment of scientific literature on this subject. (AU)

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