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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

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

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Motta Toledo, Claudio Fabiano [1] ; Arantes, Marcio da Silva [1] ; Bressan Hossomi, Marcelo Yukio [1] ; Almada-Lobo, Bernardo [2]
Total Authors: 4
[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
Total Affiliations: 2
Document type: Journal article
Source: Computers & Operations Research; v. 74, p. 92-107, OCT 2016.
Web of Science Citations: 8

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)

FAPESP's process: 11/15581-3 - Environment for development of methods applied to optimization problems
Grantee:Márcio da Silva Arantes
Support Opportunities: Scholarships in Brazil - Master
FAPESP's process: 12/00997-2 - Study and development of hybrid heuristics and metaheuristics to the multi-level capacitated lot sizing problem
Grantee:Marcelo Yukio Bressan Hossomi
Support Opportunities: Scholarships in Brazil - Scientific Initiation
FAPESP's process: 11/15534-5 - Hybrid heuristics and metaheuristics applied to the multi-level capacitated lot sizing problem
Grantee:Claudio Fabiano Motta Toledo
Support Opportunities: Regular Research Grants