Productivity improvement with parallel adjacent U-shaped assembly lines

A novel configuration of assembly lines was proposed in this research, namely parallel adjacent U‐shaped assembly lines (PAUL). Typically, in a multiple U‐ line facility, each U‐line is designed to work independently which may cause some workstations were not fully functioned. The PAUL aimed at increasing the utilisation of the whole facility by allowing cross‐trained workers to work on the opposite legs of the adjacent U‐lines (multi‐line workstations). This configuration is easier to implement than parallel U‐lines due to no restriction in terms of the lengths of U‐lines to be paralleled and hidden expenditures that could be incurred in shop floor reconstruction. Since the line balancing of the PAUL is NP‐hard and many conflicting objectives need to be optimised simultaneously, the evolutionary meta‐heuristic which was the hybridisation of the multi‐objective evolutionary algorithm based on decomposition (MOEA/D) and particle swarm optimisation (PSO), namely MOEA/D‐PSO, was developed to effectively solve the problem. In addition, the decoding algo‐ rithm to convert the solutions obtained from MOEA/D‐PSO into the PAUL’s configuration was proposed. The performance of MOEA/D‐PSO was evaluated against MOEA/D and multi‐objective particle swarm optimisation (MOPSO). The experimental results reveal that MOEA/D‐PSO outperformed its rival algorithms under the convergence‐related performance. © 2019 CPE, University of Maribor. All rights reserved.