Using variable neighbourhood descent and genetic algorithms for sequencing mixed-model assembly systems in the footwear industry

• Type: Article in International Scientific Journal
• Date: 2021

Authors

José Soeiro Ferreira (Author) FEUP; Parisa Sadeghi (Author) Other; Rui Diogo Rebelo (Author) Other

Journal

Title: Operations Research Perspectives

Vol. 8

Pages: 1-19

ISSN: 2214-7160

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 1 Citation

Other information

Authenticus ID: P-00V-37Y

DOI: 10.1016/j.orp.2021.100193

Abstract (EN): This paper addresses a new Mixed-model Assembly Line Sequencing Problem in the Footwear industry. This problem emerges in a large company, which benefits from advanced automated stitching systems. However, these systems need to be managed and optimised. Operators with varied abilities operate machines of various types, placed throughout the stitching lines. In different quantities, the components of the various shoe models, placed in boxes, move along the lines in either direction. The work assumes that the associated balancing problems have already been solved, thus solely concentrating on the sequencing procedures to minimise the makespan. An optimisation model is presented, but it has just been useful to structure the problems and test small instances due to the practical problems' complexity and dimension. Consequently, two methods were developed, one based on Variable Neighbourhood Descent, named VND-MSeq, and the other based on Genetic Algorithms, referred to as GA-MSeq. Computational results are included, referring to diverse instances and real large-size problems. These results allow for a comparison of the novel methods and to ascertain their effectiveness. We obtained better solutions than those available in the company.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 19