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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.)

Relax and fix heuristics to solve one-stage one-machine lot-scheduling models for small-scale soft drink plants

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Autor(es):
Ferreira, Deisemara [1] ; Morabito, Reinaldo [1] ; Rangel, Socorro [2]
Número total de Autores: 3
Afiliação do(s) autor(es):
[1] Univ Fed Sao Carlos, Dept Prod Engn, BR-13565905 Sao Carlos, SP - Brazil
[2] Sao Paulo State Univ, UNESP, BR-15054000 Sao Jose Do Rio Preto, SP - Brazil
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: Computers & Operations Research; v. 37, n. 4, p. 684-691, APR 2010.
Citações Web of Science: 28
Resumo

The production planning of regional small-scale soft drink plants can be modeled by mixed integer models that integrate lot sizing and scheduling decisions and consider sequence-dependent setup times and costs. These plants produce soft drinks in different flavors and sizes and they have typically only one production line. The production process is carried out basically in two main stages: liquid preparation (stage I) and bottling (stage II). However, since the production bottleneck of these plants is often in stage II, in this study we represent the problem as a one-stage one-machine lot-scheduling model that considers stage II as the bottleneck but also takes into account a capacity constraint of stage I. To solve the problem, we propose relax and fix heuristics exploring the model structure and we evaluate their computational performances solving different problem instances based on real data of a Brazilian small-scale soft drink company. The solutions obtained are compared to the company solutions and the solutions of a general-purpose optimization software. (C) 2009 Elsevier Ltd. All rights reserved. (AU)

Processo FAPESP: 04/00462-5 - Construção e solução de modelos integrados de dimensionamento e sequenciamento de lotes para a programação da produção de bebidas
Beneficiário:Deisemara Ferreira
Modalidade de apoio: Bolsas no Brasil - Doutorado