Using variable neighbourhood descent and genetic algorithms for sequencing mixed-model assembly systems in the footwear industry. (2021)

• Record Type: Journal Article
• Authors: Sadeghi, Parisa; Rebelo, Rui Diogo; Ferreira, José Soeiro
• Is Part Of: Operations research perspectives. Volume 8(2021)
• Publication Date: 2021
• Subjects: Mixed-model assembly line sequencing problem -- Variable neighbourhood descent -- Genetic algorithms -- Dispatching rules; Operations research -- Periodicals; Management science -- Periodicals; 658.403405
• DOI: 10.1016/j.orp.2021.100193
• Languages: English
• ISSNs: 2214-7160

Abstract

Abstract: 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. Highlights: New automatic footwear assembly systems, non-sequential based on real data. An optimisation model of new mixed-model assembly line sequencing problems. Operators, machines, and boxes are considered simultaneously in flexible systems. First solution approach, mainly based on a Variable Neighbourhood Descent method. Second solution method based on Genetic Algorithms.