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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Mathematical programming-based approaches for multi-facility glass container production planning

Texto completo
Autor(es):
Motta Toledo, Claudio Fabiano [1] ; Arantes, Marcio da Silva [1] ; Bressan Hossomi, Marcelo Yukio [1] ; Almada-Lobo, Bernardo [2]
Número total de Autores: 4
Afiliação do(s) autor(es):
[1] Univ Sao Paulo, Inst Ciencias Matemat & Comp, BR-13566590 Sao Carlos, SP - Brazil
[2] Univ Porto, Fac Engn, INESC TEC, P-4200465 Oporto - Portugal
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: Computers & Operations Research; v. 74, p. 92-107, OCT 2016.
Citações Web of Science: 8
Resumo

This paper introduces a mathematical model (together with a relaxed version) and solution approaches for the multi-facility glass container production planning (MF-GCPP) problem. The glass container industry covers the production of glass packaging (bottle and jars), where a glass paste is continuously distributed to a set of parallel molding machines that shape the finished products. Each facility has a set of furnaces where the glass paste is produced in order to meet the demand. Furthermore, final product transfers between facilities are allowed to face demand. The objectives include meeting demand, minimizing inventory investment and transportation costs, as well as maximizing the utilization of the production facilities. A novel mixed integer programming formulation is introduced for MF-GCPP and solution approaches applying heuristics and meta-heuristics based on mathematical programming are developed. A multi-population genetic algorithm defines for each individual the partitions of the search space to be optimized by the MIP solver. A variant of the fix-and-optimize improvement heuristic is also introduced. The computational tests are carried on instances generated from real-world data provided by a glass container company. The results show that the proposed methods return competitive results for smaller instances, comparing to an exact solver method. In larger instances, the proposed methods are able to return high quality solutions. (C) 2016 Elsevier Ltd. All rights reserved. (AU)

Processo FAPESP: 11/15581-3 - Ambiente para desenvolvimento de métodos aplicados a problemas de otimização
Beneficiário:Márcio da Silva Arantes
Modalidade de apoio: Bolsas no Brasil - Mestrado
Processo FAPESP: 12/00997-2 - Estudo e desenvolvimento de heurísticas e metaheurísticas híbridas para o problema capacitado de dimensionamento de lotes multi-nível
Beneficiário:Marcelo Yukio Bressan Hossomi
Modalidade de apoio: Bolsas no Brasil - Iniciação Científica
Processo FAPESP: 11/15534-5 - Heurísticas e metaheurísticas híbridas aplicadas ao problema capacitado de dimensionamento de lotes multi-nível
Beneficiário:Claudio Fabiano Motta Toledo
Modalidade de apoio: Auxílio à Pesquisa - Regular