Abstract
This study provides an overview of the definition of long setup times and lateness due to the wide variety of models produced in the garment industry, the solutions developed to solve these problems, and the designs to be proposed. The setup times of the product produced in the Multi-Model Assembly Line vary according to the model type. In this study, we considered a single machine as an assembly line and adapted Single Machine Scheduling with Sequence-Dependent setup times problem to Multi-Model Assembly Line Sequencing with sequence-dependent setup times problem for the garment industry. To solve this problem, we used two different solution techniques: Meta-Heuristic Algorithms and a mathematical model that includes the setup process and lateness accordingly suggested. Two different metaheuristic algorithms, Tabu Search and Simulated Annealing were used in this paper. SA algorithm, Tabu Search Algorithm, and mathematical model were used to find optimal and near-optimal results, which were compared. The metaheuristic achieved favourable solutions when comparing the results with mathematical model results. The mathematical model suggested was solved utilizing version 20.1 of ILOG CPLEX OPTIMIZATION STUDIO. The simulated Annealing and Tabu Search algorithm suggested were solved utilizing version R2023a of MATLAB. The obtained results are compared with respect to solution quality and computational time.
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Kuzu, T. et al. (2024). Application of Meta-heuristic Algorithms for Sequencing Multi-model Assembly Line with Sequence-Dependent Setup Time in Garment Industry. In: Durakbasa, N.M., Gençyılmaz, M.G. (eds) Industrial Engineering in the Industry 4.0 Era. ISPR 2023. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-53991-6_54
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