Algorithms | |
A Hybrid Metaheuristic Approach for Minimizing the Total Flow Time in A Flow Shop Sequence Dependent Group Scheduling Problem | |
Antonio Costa1  Fulvio Antonio Cappadonna2  | |
[1] University of Catania, DII, V.le A. Doria 6, 95125 Catania, Italy; E-Mail:;University of Catania, DIEEI, V.le A. Doria 6, 95125 Catania, Italy; E-Mail: | |
关键词: cellular manufacturing; genetic algorithm; encoding; decoding; sequencing; | |
DOI : 10.3390/a7030376 | |
来源: mdpi | |
【 摘 要 】
Production processes in Cellular Manufacturing Systems (CMS) often involve groups of parts sharing the same technological requirements in terms of tooling and setup. The issue of scheduling such parts through a flow-shop production layout is known as the Flow-Shop Group Scheduling (FSGS) problem or, whether setup times are sequence-dependent, the Flow-Shop Sequence-Dependent Group Scheduling (FSDGS) problem. This paper addresses the FSDGS issue, proposing a hybrid metaheuristic procedure integrating features from Genetic Algorithms (GAs) and Biased Random Sampling (BRS) search techniques with the aim of minimizing the total flow time,
【 授权许可】
CC BY
© 2014 by the authors; licensee MDPI, Basel, Switzerland.
【 预 览 】
Files | Size | Format | View |
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RO202003190023978ZK.pdf | 276KB | download |