Abstract
ABSTRACT This paper addresses a lot sizing problem in a Brazilian chemical industry where a product can be produced by more than one process, which can use different parallel machines and may even consume a wide range of raw materials. Moreover, most of the products are liquids and the inventories must be kept in a restricted number of storage tanks with a limited capacity. Hence, these two issues are barely addressed in the literature on lot sizing. The classical multi-level capacitated lot sizing problem was extended to address them and a mixed integer programming (MIP) formulation was developed to determine how many batches should be produced and in which tank products should be stored to meet the demands and minimize production costs. The results of computational experiments show that the commercial solver found poor quality solutions or could not find feasible solutions within one hour. Thus, we applied relaxand-fix and fix-and-optimize MIP based heuristics and we observed that these heuristics were able to obtain feasible solutions for more instances in shorter computational times and find better solutions than those obtained by the commercial solver to solve the proposed model.
Highlights
Production planning is one of the most important decision-making levels in the manufacturing industry and can be considered an essential tool tool to improve its (Li, Gao, Shao, Zhang & Wang, 2010) operating activities and one of the main keys to a company’s success
Billington, McClain & Thomas (1983) were pioneers regarding the discussion on the multi-level capacitated lot sizing problem (MLCLSP) and after their work, many studies emerged
This study focuses on the medium-term production planning based on a Brazilian chemical industry
Summary
Production planning is one of the most important decision-making levels in the manufacturing industry and can be considered an essential tool tool to improve its (Li, Gao, Shao, Zhang & Wang, 2010) operating activities and one of the main keys to a company’s success. Gunther & Lehmann (2002) studied the production planning problem in a pharmaceutical and chemical industry with a batch and multi-level production line system. Cooke & Rohleder (2006) dealt with the lot sizing and scheduling problems of an industry with continuous processing and multiple plants to regulate inventory levels and quantities produced in each plant. Studies related to the process industry generally address scheduling problems (Blomer & Gunther (1998, 2000)) or long term decisions (Mostafaei & Ghaffari Hadigheh (2014)). Classical lot sizing problems do not take into account inventory storage tank constraints during the production process of intermediate and final products (see Karimi et al (2003), Chen (2015a), Furlan & Santos (2015)). In this paper, we deal with a multi-level lot sizing problem where an item can be produced adopting several processes with limited resources for production and storage of items. We developed relax-and-fix and fix-andoptimize heuristics, which have shown promising results for the instances generated based on real data
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