Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Yu, Shun-Chi; *
Affiliations: International College, Krirk University, Bangkok, Thailand
Correspondence: [*] Corresponding author. Shun-Chi Yu, International College, Krirk University, 3 Ram Inthra Rd, Anusawari, Bang Khen, Bangkok 10220, Thailand. E-mail: [email protected].
Abstract: In the recent decades, genetic algorithms (GAs) have often been applied as heuristic techniques at various settings entailing production scheduling. However, early convergence is one of the problems associated with this approach. This study develops an efficient local search rule for the target-oriented rule in traditional GAs. It also addresses the problem of two-stage multiprocessor flow-shop scheduling (FSP) by viewing the due window and sequence-dependent setup times as constraints faced by common flow shops with multiprocessor scheduling suites in the actual production scenario. Using the simulated data, this study verifies the effectiveness and robustness of the proposed algorithm. The results of data testing demonstrate that the proposed method may outperform other algorithms, including a significant hybrid algorithm, in addressing the problems considered.
Keywords: Target-oriented, genetic algorithm, two-stage multiprocessor flow shop scheduling, due window, setup time
DOI: 10.3233/JIFS-220174
Journal: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 5, pp. 6213-6228, 2022
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]