Abstract
Given that group technology can reduce the changeover time of equipment, broaden the productivity, and enhance the flexibility of manufacturing, especially cellular manufacturing, group scheduling problems (GSPs) have elicited considerable attention in the academic and industry practical literature. There are two issues to be solved in GSPs: One is how to allocate groups into the production cells in view of major setup times between groups and the other is how to schedule jobs in each group. Although a number of studies on GSPs have been published, few integrated reviews have been conducted so far on considered problems with different constraints and their optimization methods. To this end, this study hopes to shorten the gap by reviewing the development of research and analyzing these problems. All literature is classified according to the number of objective functions, number of machines, and optimization algorithms. The classical mathematical models of single-machine, permutation, and distributed flowshop GSPs based on adjacent and position-based modeling methods, respectively, are also formulated. Last but not least, outlooks are given for outspread problems and problem algorithms for future research in the fields of group scheduling.
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This work is partially supported by the National Natural Science Foundation of China (Grant Nos. 61803192, 61966012, 61973203, and 62106073), Guangyue Young Scholar Innovation Team of Liaocheng University (Grant No. LCUGYTD2022-03), the Youth Innovation Talent Introduction and Education Program support from Shandong Province Colleges and Universities, the Natural Science Foundation of Hunan Province (Grant No. 2021JJ40116), and the Natural Science Foundation of Shandong Province (Grant Nos. ZR2021QE195 and ZR2021QF036).
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Wang, Y., Han, Y., Gong, D. et al. A review of intelligent optimization for group scheduling problems in cellular manufacturing. Front. Eng. Manag. 10, 406–426 (2023). https://doi.org/10.1007/s42524-022-0242-0
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DOI: https://doi.org/10.1007/s42524-022-0242-0