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Title: Assembly line balancing based on beam ant colony optimisation
Authors: Huo, JG 
Wang, ZX
Chan, FTS 
Lee, CKM 
Strandhagen, JO
Issue Date: 2018
Publisher: Hindawi Publishing Corporation
Source: Mathematical problems in engineering, 2018, 2481435, p. 1-17 How to cite?
Journal: Mathematical problems in engineeringprint+eissn 
Abstract: We use a hybrid approach which executes ant colony algorithm in combination with beam search (ACO-BS) to solve the Simple Assembly Line Balancing Problem (SALBP). The objective is to minimise the number of workstations for a given fixed cycle time, in order to improve the solution quality and speed up the searching process. The results of 269 benchmark instances show that 95.54% of the problems can reach their optimal solutions within 360 CPU time seconds. In addition, we choose order strength and time variability as indicators to measure the complexity of the SALBP instances and then generate 27 instances with a total of 400 tasks (the problem size being much larger than that of the largest benchmark instance) randomly, with the order strength at 0.2, 0.6 and 0.9 three levels and the time variability at 5-15, 65-75, and 135-145 levels. However, the processing times are generated following a unimodal or a bimodal distribution. The comparison results with solutions obtained by priority rule show that ACO-BS makes significant improvements on the quality of the best solutions.
ISSN: 1024-123X
EISSN: 1563-5147
DOI: 10.1155/2018/2481435
Rights: Copyright © 2018 JiageHuo et al.This is an open access article distributed under the Creative CommonsAttribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The following publication Huo, J.G., Wang, Z.X., Chan, F.T.S., Lee, C.K.M., & Strandhagen, J.O. (2018). Assembly line balancing based on beam ant colony optimisation. Mathematical problems in engineering, 2481435, 1-17 is available at
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