Title: A genetic algorithm-based robust approach for type-II U-shaped assembly line balancing problem

Authors: Guangyue Jia; Honghui Zhan; Yunfang Peng

Addresses: CRRC Qingdao Sifang Co., Ltd., Qingdao, China ' Wuxi Research Institute, Huazhong University of Science and Technology, Wuxi, China ' School of Management, Shanghai University, Shanghai, China

Abstract: U-shaped assembly lines are widely used to implement just-in-time manufacturing. U-shaped assembly line balancing problem is important to improve productivity. Most of the studies ignore uncertainty such as operation times. This study applies robust optimisation method to deal with type-II U-shaped assembly line balancing problem (UALBP-2) under uncertainty. A mathematical programming model is proposed with interval task operation times, and a genetic algorithm is developed to deal with it. A robust solution is defined as the most frequent solution falling within a pre-specified percentage of the optimal solution for different sets of scenarios. The experimental results are compared with the expected solution to verify the feasibility and effectiveness of the robust method.

Keywords: U-shaped assembly line; mathematical programming; robust solution; genetic algorithm.

DOI: 10.1504/IJICA.2022.128437

International Journal of Innovative Computing and Applications, 2022 Vol.13 No.5/6, pp.296 - 302

Received: 22 Jun 2020
Accepted: 23 Nov 2020
Published online: 23 Jan 2023 *

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