AUGMECON2 method for a Bi-objective U-shaped assembly line balancing problem

Abstract

This study explores the bi-objective U-shaped assembly line balancing problem (UALBP) by considering several scenarios constructed based on worker skill levels. Because the investigated problem has two objectives, namely the minimizing the number of stations and maximum workload imbalance, an improved ε-constrained based method is employed to find the Pareto-optimal solutions to the problem. This method is called to be the second version of the augmented ε-constrained (AUGMECON2) and it is highly effective to find the Pareto-optimal solutions within reasonable CPU time. In order to investigate the impact of workers’ inherent on both of the objectives, a set of scenarios is considered. Each scenario is determined based on the nature of the worker pool in which workers are assigned to the stations. An optimization model is presented for the problem and it is solved with a real case study from the industry. The computational results indicate that the scenarios have a great impact on the workload imbalance objective. In particular, it is revealed that while the skill levels of workers increases, the workload imbalance decreases. However, the same impact is not observed for the number of stations.