Evaluation of rank-based crossovers to optimize real-life assembly line balancing with resource constraint

• Main Authors: K. H., Khalib, Nur Hairunnisa, Kamarudin, M. F. F., Ab Rashid
• Format: Conference or Workshop Item
• Language: English
• Published: IOP Publishing 2019
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://umpir.ump.edu.my/id/eprint/24526/1/Evaluation%20of%20rank-based%20crossovers%20to%20optimize%20real-life%20assembly%20line%20balancing%20with%20resource%20constraint.pdf; http://umpir.ump.edu.my/id/eprint/24526/; https://doi.org/10.1088/1757-899X/469/1/012014

Assembly line balancing (ALB) problem has evolved in lined with the manufacturing advancement. Previous research in ALB mostly assumed that all workstations are having similar capabilities including the machines, tools and worker skills. Recently, researchers started to consider the ALB with resource constraint (ALB-RC) such as machine and worker. This paper aim to evaluate new rank-based crossovers to optimize real-life ALB-RC problem. Prior to this work, the authors had proposed rank-based crossover type I and II (RBC-I and II) to enhance the performance of Genetic Algorithm (GA) in optimizing ALB-RC problem. An industrial case study has been conducted in electronics industry. The results of industrial case study confirmed that the proposed ALB-RC model is capable to be used for the real industrial problem. At the same time, the result indicated that the GA with rank-based crossover is capable to optimize real-life problem. As a comparison, the number of workstation, resources and workers had reduced between 10 – 15% for the optimised layout using GA with RBC, compared with the original layout in the case study problem.