| Full text | |
| Author(s): |
Total Authors: 2
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| Affiliation: | [1] Univ Fed Sao Paulo UNIFESP, Inst Ciencia & Tecnol, Ave Cesare G Lattes 1201, Sao Jose Dos Campos, SP - Brazil
Total Affiliations: 1
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| Document type: | Journal article |
| Source: | Computers & Operations Research; v. 71, p. 137-148, JUL 2016. |
| Web of Science Citations: | 4 |
| Abstract | |
Production planning plays an important role in the industrial sector. The focus of this paper is on the lot sizing of those companies composed by multiple plants, each of them with a finite planning horizon divided into periods. All plants produce the same items and have their demands to be met without delay. For producing items, all plants have a single machine with setup times and costs and a limited capacity of production. Transfers of production lots among plants and storage of items are allowed. Even though there are some studies to tackle this problem, to find feasible solutions for the entire set of benchmark instances remains a challenge. This paper introduces novel Lagrangian heuristics that, besides heuristically solving all benchmark instances, significantly outperformed the best heuristic from the literature. (C) 2016 Elsevier Ltd. All rights reserved. (AU) | |
| FAPESP's process: | 15/21660-4 - Hibridizing heuristic and exact methods to approach combinatorial optimization problems |
| Grantee: | Mariá Cristina Vasconcelos Nascimento Rosset |
| Support Opportunities: | Regular Research Grants |