Many-Objective Parallel Adjacent U-shaped Assembly Line Balancing Operated by Human and Robot

Abstract

This research is considered to the Parallel Adjacent U-line(PAUL), which operated by human and robot. Both resources are extensively used in the manufacturing industry. The PAUL is proposed to increase the utilisation of the assembly line because it can use assigned resources for operation between the adjacent U-line (Multi-line workstation). In the line balancing, allocation of tasks, robots, regular workers and disabled workers on the PAUL is known as NP-hard problems. Many conflicting objectives need to optimize simultaneously. The most effective solution to these problems is the meta-heuristic. According to optimize the problem in time limiting, Non-dominated Sorting Genetic Algorithm tree (NSGA-III) is applied to solve the problems. As the result, a comparison between the performance of NSGA-III and MOEA/D by considering GD and IGD metrics showed that NSGA-III were outperformed under GD and IGD metrics for all problems.