Intelligent Benders’ Decomposition Algorithm for Sequencing Multi-model Assembly Line with Sequence Dependent Setup Times Problem: A Case Study in a Garment Industry

Abstract

In recent years clothing manufactures aim at producing various of products with low stock in order to meet customer demand. Besides this fact the ready-made clothing industry needs to pursue science technology and innovation policies to keep up with the rapid change in the fashion industry. One of the most commonly used production systems in garment industry is assembly lines where parts are subsequently added until the end product is obtained. In garment industry on time delivery plays a vital role in increasing customer satisfaction while ensuring demand. Consequently setup times in assembly lines are of paramount importance to track the performance of production system. In this study the minimization problem of long setup times due to the wide variety of models produced in the garment industry is handled. A real-life production management problem is defined formulated as an MIP model and solved to improve customer delivery rate and to increase efficiency by minimizing setup time. To solve this problem to optimality two exact solution techniques namely Branch and Bound and Benders’ Decomposition Techniques are taken into consideration. The proposed mathematical model is solved with ILOG CPLEX OPTIMIZATION STUDIO version 20.1 and the solutions obtained using each technique are compared with respect to solution quality and computational time. © 2023 Elsevier B.V. All rights reserved.