Research on Production Scheduling Optimization of Flexible Job Shop Production with Buffer Capacity Limitation Based on the Improved Gene Expression Programming Algorithm
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Mechanical Engineering
Link
https://link.springer.com/content/pdf/10.1007/s12541-023-00897-2.pdf
Reference42 articles.
1. Cao, Y., Feng, Z., & Jiang, Q. (2020). Automatic data acquisition technology for SMT manufacturing based on multi-variety and small-batch. In Lecture Notes in Electrical Engineering.
2. Zhang, G. B., Li, L. Z., Ran, Y., & Xiao, Y. L. (2018). Process capability analysis based on similarity cell under the multiple-variety and small-batch production mode. Chinese Journal of Engineering Design. https://doi.org/10.3785/j.issn.1006-754X.2018.01.003
3. Zhou, Y., Yang, J. J., & Zheng, L. Y. (2019). Hyper-heuristic coevolution of machine assignment and job sequencing rules for multi-objective dynamic flexible job shop scheduling. IEEE Access. https://doi.org/10.1109/ACCESS.2018.2883802
4. Cao, Y., Shi, H., & Chang, D. L. (2022). Differential evolution algorithm with dynamic multi-population applied to flexible job shop schedule. Engineering Optimization. https://doi.org/10.1080/0305215X.2021.1872067
5. Yin, L., Zhang, W., & Zhou, T. (2023). Machine health-driven dynamic scheduling of hybrid jobs for flexible manufacturing shop. International Journal of Precision Engineering and Manufacturing. https://doi.org/10.1007/s12541-023-00784-w
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