Development of Framework for Flexible Job Shop Scheduling Based on Digital Twin to Tackle Disturbing Events
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-1245-2_30
Reference31 articles.
1. Zhang M, Tao F, Nee AJJoMS (2021) Digital twin enhanced dynamic job-shop scheduling 58:146–156
2. Saqlain M et al (2022) A monte-carlo tree search algorithm for the flexible job-shop scheduling in manufacturing systems, p 1–24
3. Zhang F et al (2021) Collaborative multifidelity-based surrogate models for genetic programming in dynamic flexible job shop scheduling
4. Fangfang Z, Yi M, Mengjie Z (2019) A new representation in genetic programming for evolving dispatching rules for dynamic flexible job shop scheduling. EvoCOP
5. Lilan L et al (2022) Digital twin-driven adaptive scheduling for flexible job shops. Sustainability
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