Balancing apparel assembly lines through adaptive ant colony optimization

Abstract

The goal of this study was to introduce an effective optimization method to balancing one-piece flow assembly lines by rearranging manufacturing tasks necessary for an apparel production to minimize the number of workstations and the idle time of the assembly line under certain conditions. In this paper, we firstly define an assembly-line-balancing (ALB) problem in apparel production and established an objective function for minimizing the smoothness index, a term that measures the difference between the worktime and the targeted cycle time of each workstation on an assembly line. We then illustrate an adaptive ant colony (AAC) algorithm with modifications made on the traditional ant colony algorithm for solving the ALB problem. Finally, we present the experiments using real-world data provided by an apparel manufacturer to compare the results generated from the AAC and the prior practice of the company. It was demonstrated that the AAC could help the company reduce the number of workstations on its assembly lines and cut the idle time at most of the workstations.