Digital twin for energy-efficient integrated process planning and scheduling
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Software,Control and Systems Engineering
Link
https://link.springer.com/content/pdf/10.1007/s00170-023-11755-w.pdf
Reference41 articles.
1. Karimi S, Ardalan Z, Naderi B, Mohammadi M (2017) Scheduling flexible job-shops with transportation times: mathematical models and a hybrid imperialist competitive algorithm. Appl Math Model 41:667–682. https://doi.org/10.1016/j.apm.2016.09.022
2. Liu QH, Li XY, Gao L, Wang GC (2022) A multiobjective memetic algorithm for integrated process planning and scheduling problem in distributed heterogeneous manufacturing systems. Memet Comput 14(2):193–209. https://doi.org/10.1007/s12293-022-00364-x
3. Zhang LP, Yu CX, Wong TN (2019) Cloud-based frameworks for the integrated process planning and scheduling. Int J Computer Integr Manuf 32(12):1192–1206. https://doi.org/10.1080/0951192x.2019.1690682
4. Tao F, Qi QG, Wang LH, Nee AYC (2019) Digital twins and cyber-physical systems toward smart manufacturing and industry 4.0: correlation and comparison. Eng 5(4):653–661. https://doi.org/10.1016/j.eng.2019.01.014
5. Zhu H, Deng QW, Zhang LK, Hu X, Lin WH (2020) Low carbon flexible job shop scheduling problem considering worker learning using a memetic algorithm. Optim Eng 21(4):1691–1716. https://doi.org/10.1007/s11081-020-09494-y
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