Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/8189
Title: A genetic-algorithm-based optimization model for solving the flexible assembly line balancing problem with work sharing and workstation revisiting
Authors: Guo, ZX
Wong, WK 
Leung, SYS 
Fan, JT
Chan, SF
Issue Date: 2008
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on systems, man, and cybernetics. Part C, Applications and reviews, 2008, v. 38, no. 2, p. 218-228 How to cite?
Journal: IEEE transactions on systems, man, and cybernetics. Part C, Applications and reviews 
Abstract: This paper investigates a flexible assembly line balancing (FALB) problem with work sharing and workstation revisiting. The mathematical model of the problem is presented, and its objective is to meet the desired cycle time of each order and minimize the total idle time of the assembly line. An optimization model is developed to tackle the addressed problem, which involves two parts. A bilevel genetic algorithm with multiparent crossover is proposed to determine the operation assignment to workstations and the task proportion of each shared operation being processed on different workstations. A heuristic operation routing rule is then presented to route the shared operation of each product to an appropriate workstation when it should be processed. Experiments based on industrial data are conducted to validate the proposed optimization model. The experimental results demonstrate the effectiveness of the proposed model to solve the FALB problem.
URI: http://hdl.handle.net/10397/8189
ISSN: 1094-6977
DOI: 10.1109/TSMCC.2007.913912
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