| Automatic design of dispatching rules for real-time optimization of complex production systems Z Shi, S Gao, J Du, H Ma, L Shi 2019 IEEE/SICE international symposium on system integration (SII), 55-60, 2019 | 8 | 2019 |
| Workforce allocation in motorcycle transmission assembly lines: A case study on modeling, analysis, and improvement H Ma, HK Lee, Z Shi, J Li IEEE Robotics and Automation Letters 5 (3), 4164-4171, 2020 | 7 | 2020 |
| A learning-based two-stage optimization method for customer order scheduling Z Shi, H Ma, M Ren, T Wu, JY Andrew Computers & Operations Research 136, 105488, 2021 | 6 | 2021 |
| Compressive-sensing-assisted mixed integer optimization for dynamical system discovery with highly noisy data Z Shi, H Ma, H Tran, G Zhang arXiv preprint arXiv:2209.12663, 2022 | 3 | 2022 |
| A Physics-informed Machine Learning-based Control Method for Nonlinear Dynamic Systems with Highly Noisy Measurements M Ma, J Wu, C Post, T Shi, J Yi, T Schmitz, H Wang arXiv preprint arXiv:2311.07613, 2023 | 1 | 2023 |
| AFSD-Nets: A Physics-informed Machine Learning Model for Predicting the Temperature Evolution During Additive Friction Stir Deposition T Shi, J Wu, M Ma, E Charles, T Schmitz Available at SSRN 4627557, 2023 | 1 | 2023 |
| AFSD-Physics: Exploring the governing equations of temperature evolution during additive friction stir deposition by a human-AI teaming approach T Shi, M Ma, J Wu, C Post, E Charles, T Schmitz arXiv preprint arXiv:2401.16501, 2024 | | 2024 |
| Integration of discrete-event dynamics and machining dynamics for machine tool: Modeling, analysis and algorithms M Ma, A Ren, C Tyler, J Karandikar, M Gomez, T Shi, T Schmitz Manufacturing Letters 35, 321-332, 2023 | | 2023 |
| A Simulation Optimization-Aided Learning Method for Design Automation of Scheduling Rules H Ma, C Zhang, Z Shi 2022 IEEE 18th International Conference on Automation Science and …, 2022 | | 2022 |
Tony Z. ShiUniversity of Tennessee, KnoxvilleVerified email at utk.edu
