| Full text | |
| Author(s): |
Artur Lovato Cunha
[1]
;
Maristela Oliveira Santos
Total Authors: 2
|
| Affiliation: | [1] Universidade de São Paulo. Instituto de Ciências Matemáticas e de Computação - Brasil
Total Affiliations: 2
|
| Document type: | Journal article |
| Source: | Pesquisa Operacional; v. 37, n. 2, p. 311-331, 2017-08-00. |
| 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. (AU) | |
| FAPESP's process: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | Francisco Louzada Neto |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |