期刊名称：Journal of Open Innovation: Technology, Market, and Complexity
电子版ISSN：2199-8531
出版年度：2020
卷号：6
期号：1
页码：1-22
DOI：10.3390/joitmc6010021
语种：English
出版社：Springer
摘要：This article aims to minimize cycle time for a simple assembly line balancing problem type 2 by presenting a variable neighborhood strategy adaptive search method (VaNSAS) in a case study of the garment industry considering the number and types of machines used in each workstation in a simple assembly line balancing problem type 2 (SALBP-2M). The variable neighborhood strategy adaptive search method (VaNSAS) is a new method that includes five main steps, which are (1) generate a set of tracks, (2) make all tracks operate in a specified black box, (3)operate the black box, (4) update the track, and (5) repeat the second to fourth steps until the termination condition is met. The proposed methods have been tested with two groups of test instances, which are datasets of (1) SALBP-2 and (2) SALBP-2M. The computational results show that the proposed methods outperform the best existing solution found by the LINGO modeling program. Therefore, the VaNSAS method provides a better solution and features a much lower computational time.
关键词：variable neighborhood strategy adaptive search; simple assembly line balancing problem type 2; cycle time
