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

• Type: Article in International Scientific Journal
• Date: 2016

Authors

Claudio Fabiano Motta Toledo (Author) Other; Marcio da Silva Arantes (Author) Other; Marcelo Yukio Bressan Hossomi (Author) Other; Bernardo Almada Lobo (Author) FEUP

Journal

Title: Computers and Operations Research

Vol. 74

Pages: 92-107

ISSN: 0305-0548

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 11 Citations

ISI Web of Science

Scopus - 11 Citations

Scientific classification

CORDIS: Technological sciences

FOS: Engineering and technology

Other information

Authenticus ID: P-00K-NK6

DOI: 10.1016/j.cor.2016.02.019

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 16