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

This paper addresses a new Mixed-model Assembly Line Sequencing Problem in the Footwear industry. problem emerges 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 lines. In different quantities, components shoe models, boxes, move along lines either direction. The work assumes that associated balancing problems have already been solved, thus solely concentrating on sequencing procedures minimise makespan. An optimisation model is presented, but it has just useful structure test small instances due practical problems’ complexity dimension. Consequently, two methods were developed, one based Variable Neighbourhood Descent, named VND-MSeq, other Genetic Algorithms, referred as GA-MSeq. Computational results are included, referring diverse real large-size problems. These allow for comparison novel ascertain their effectiveness. We obtained better solutions than those available company.