( † students supervised, *corresponding author)
Under Review
[R4]. T. Shi* and T. Schmitz, “ChatterStabilizer: An Accurate and Scalable Framework of Bifurcation and Stability Analysis for Advancing Machine Tool Chatter Theory and Applications”, Under review at ASME Journal of Manufacturing Science and Engineering, 2025.
[R3]. M. Ma†, V. Wu†, J. Yi, H. Wang, B. Jared, T. Schmitz and T. Shi*, “An Interpretable Machine Learning based Predictive Control Method for Manufacturing Processes with Turning as A Case Study”, Under review at NAMRC 54, 2025.
[R2]. M. Shataraha, K. Liu, T. Shi, H. Li*, “Operator-based Machine Learning Framework for Generalizable Prediction of Unsteady Treatment Dynamics in Stormwater Infrastructure”, Under review at Journal of Environmental Engineering, 2025.
[R1]. H. Zhang, H. Xiao*, G. Kou and T. Shi, “Dynamic Simulation Budget Allocation for the Best and Worst Subsets Selection of Complex System Designs”, Under review at Naval Research Logistics, 2025.
Articles Published at UTK
[J30]. V. Wu†, M. Ma†, J. Karandikar, C. Tyler, T. Shi* and T. Schmitz, “An Analytical Model Integrating Tool Kinematics and Material Flow for Spindle Torque Prediction in Additive Friction Stir Deposition”, Manufacturing Letters, 44, 1177-1186, 2025, https://doi.org/10.1016/j.mfglet.2025.06.137.
[J29]. A. Ren†, M. Ma†, V. Wu†, J. Karandikar, C. Tyler, C., T. Shi* and T. Schmitz, “A Cutting Mechanics-based Machine Learning Modeling Method to Discover Governing Equations of Machining Dynamics”, Manufacturing Letters, 44, 759-769, 2025, https://doi.org/10.1016/j.mfglet.2025.06.089.
[J28]. W. Wang, J. Li, L. Ding, J. Wu†, M. Ma†, T. Shi, M. Mench, F. Zhang*, “3D Multiphysics Modeling for Probing the Non-homogenous Parameter Distribution in Proton Exchange Membrane Electrolyzer Cells”, Energy Conversion and Management, 324, 119222, 2025, https://doi.org/10.1016/j.enconman.2024.119222.
[J27]. T. Shi, H. Ma†, H. Tran and G. Zhang*, “Compressive-Sensing-assisted Mixed Integer Optimization for Dynamical System Discovery with Highly Noisy Data”, Numerical Methods for Partial Differential Equations, 41(1):e23164, 2025, https://doi.org/10.1002/num.23164.
[J26]. T. Shi*, H. Ma†, J. Wu†, C. Post†, E. Charles and T. Schmitz, “AFSD-Physics: Exploring the Governing Equations of Temperature Evolution during Additive Friction Stir Deposition by A Human-AI Teaming Approach”, Manufacturing Letters, 41, 1004-1015, 2024, https://doi.org/10.1016/j.mfglet.2024.09.125.
[J25]. T. Shi*, J. Wu†, H. Ma†, E. Charles and T. Schmitz, “AFSD-Nets: A Physics-Informed Machine Learning Model for Predicting the Temperature Evolution during Additive Friction Stir Deposition”, ASME Journal of Manufacturing Science and Engineering, 146(8), 081003, 2024, https://doi.org/10.1115/1.4065178.
[J24]. M. Ma†, A. Ren†, C. Tyler, J. Karandikar, M. Gomez, T. Shi* and T. Schmitz, “Integration of Discrete-event Dynamics and Machining Dynamics for Machine Tool: Modeling, Analysis and Algorithms”, Manufacturing Letters, 35:321-332, 2023, https://doi.org/10.1016/j.mfglet.2023.08.096.
[J23]. Y. Li, S. Gao* and T. Shi, “Asymptotic Optimality of Myopic Ranking and Selection Procedures”, Automatica, 151: 110896, 2023, https://doi.org/10.1016/j.automatica.2023.110896.
[J22]. Z. Shi, Y. Peng*, L. Shi, C.H. Chen and M. Fu, “Dynamic Sampling Allocation under Finite Simulation Budget for Feasibility Determination”, INFORMS Journal on Computing, 34(1): 557-568, 2022, https://doi.org/10.1287/ijoc.2020.1057.
[J21]. Z. Shi*, H. Ma†, M. Ren†, T. Wu and A.J. Yu, “A Learning-based Two-stage Optimization Method for Customer Order Scheduling”, Computers and Operations Research, 136:105488, 2021, https://doi.org/10.1016/j.cor.2021.105488.
[J20]. T. Wu, Z. Shi and C. Zhang*, “The Intermodal Hub Location Problem with Market Selection”, Computers and Operations Research, 127: 105136, 2021, https://doi.org/10.1016/j.cor.2020.105136.
[J19]. M. Qin, Z. Shi*, W. Chen, S. Gao and L. Shi, “Wafer Defect Inspection Optimization with Partial Coverage - A Numerical Approach”, IEEE Transactions on Automation Science and Engineering, 18(4), pp.1916-1927, 2020, 10.1109/TASE.2020.3024651.
[J18]. T. Wu, Z. Shi, Z. Liang*, X. Zhang and C. Zhang, “Dantzig-Wolfe Decomposition for the Facility Location and Production Planning Problem”, Computers and Operations Research, 124: 105068, 2020, https://doi.org/10.1016/j.cor.2020.105068.
[J17]. H. Ma†, H.K. Lee, Z. Shi and J. Li*, “Workforce Allocation in Motorcycle Transmission Assembly Lines: A Case Study on Modeling, Analysis, and Improvement”, IEEE Robotics and Automation Letters 5(3): 4164-4171, 2020, 10.1109/LRA.2020.2989658.
[J16]. M. Qin, R. Wang, Z. Shi*, L. Liu, and L. Shi, “A Genetic Programming based Scheduling Approach for Hybrid Flow Shop with a Batch Processor and Waiting Time Constraint”, IEEE Transactions on Automation Science and Engineering, 8(1), pp.94-105, 2019, 10.1109/TASE.2019.2947398.
[J15]. Z. Shi, S. Gao*, H. Xiao and W. Chen, “A Worst-Case Formulation for Constrained Ranking and Selection with Input Uncertainty”, Naval Research Logistics, 66(8): 648-662, 2019, https://doi.org/10.1002/nav.21871.
[J14]. F. Gao, Z. Shi, S. Gao* and H. Xiao, “Efficient Simulation Budget Allocation for Subset Selection Using Regression Metamodels”, Automatica, 106: 192-200, 2019, https://doi.org/10.1016/j.automatica.2019.05.022.
Articles Published Before Joining UTK
[J13]. W. Wang, Z. Shi*, L. Shi and Q. Zhao, “Integrated Optimization on Flow Shop Production with Cutting Stock”, International Journal of Production Research, 57(19): 5996-6012, 2019, https://doi.org/10.1080/00207543.2018.1556823.
[J12]. Y. Peng, E. Huang, J. Xu, Z. Shi* and C.H. Chen, “A Coordinate Optimization Approach for Concurrent Design”, IEEE Transactions on Automatic Control, 64(7): 2913 - 2920, 2019, 10.1109/TAC.2018.2872196.
[J11]. F. Gao, S. Gao*, H. Xiao and Z. Shi, “Advancing Constrained Ranking and Selection with Regression in Partitioned Domains”, IEEE Transactions on Automation Science and Engineering, 16(1): 382 - 391, 2019, 10.1109/TASE.2018.2811809.
[J10]. Z. Shi*, Z. Huang and L. Shi, “Customer Order Scheduling on Batch Processing Machines with Incompatible Job Families”, International Journal of Production Research, 56(1-2): 795-808, 2018, https://doi.org/10.1080/00207543.2017.1401247.
[J9]. L. Liu, Z. Shi and L. Shi*, “Minimization of Total Energy Consumption in an m-machine Flow Shop with an Exponential Time-Dependent Learning Effect”, Frontiers of Engineering Management, 5(4): 487-498, 2018, 10.15302/J-FEM-2018042.
[J8]. Z. Huang, Z. Shi* and L. Shi, “Minimizing Total Weighted Completion Time on Batch and Unary Processors with Incompatible Job Families”, International Journal of Production Research, 57(2): 567-581, 2018, https://doi.org/10.1080/00207543.2018.1470341.
[J7]. Y. Zhao, X. Zhang*, Z. Shi and L. He, “Grain Price Forecasting using a Hybrid Stochastic Method”, Asia-Pacific Journal of Operational Research, 34(05): 1750020, 2017, https://doi.org/10.1142/S0217595917500208.
[J6]. P. Liu, X. Zhang*, Z. Shi and Z. Huang, “Simulation Optimization for MRO Systems Operations”, Asia-Pacific Journal of Operational Research, 34(02): 1750003, 2017, https://doi.org/10.1142/S0217595917500038.
[J5]. Z. Shi, Z. Huang and L. Shi*, “Two-Stage Scheduling on Batch and Single Machines with Limited Waiting Time Constraint”, Frontiers of Engineering Management, 4(3): 368-374, 2017, 10.15302/J-FEM-2017034.
[J4]. C. Zhang, Z. Shi*, Z. Huang, Y. Wu and L. Shi, “Flow Shop Scheduling with a Batch Processor and Limited Buffer”, International Journal of Production Research, 55(11): 3217-3233, 2017, https://doi.org/10.1080/00207543.2016.1268730.
[J3]. Z. Huang, Z. Shi*, C. Zhang and L. Shi, “A Note on “Two New Approaches for a Two-stage Hybrid Flowshop Problem with a Single Batch Processing Machine under Waiting Time Constraint”, Computers & Industrial Engineering, 110: 590-593, 2017, https://doi.org/10.1016/j.cie.2017.04.010.
[J2]. Z. Shi*, L. Wang, P. Liu and L. Shi, “Minimizing Completion Time for Order Scheduling: Formulation and Heuristic Algorithm”, IEEE Transactions on Automation Science and Engineering, 14(4): 1558-1569, 2017, 10.1109/TASE.2015.2456131.
[J1]. J. Song, Z. Shi*, B. Sun and L. Shi, “Treatment Planning for Volumetric-modulated Arc Therapy: Model and Heuristic Algorithms”, IEEE Transactions on Automation Science and Engineering, 12(1): 116-126, 2015, 10.1109/TASE.2014.2360530.
[C7]. H. Ma†, C. Zhang† and Z. Shi*, “A Simulation Optimization-Aided Learning Method for Design Automation of Scheduling Rules”, Proceedings of the 2022 IEEE Conference on Automation Science and Engineering, pp. 1992-1997, 2022, 10.1109/CASE49997.2022.9926615.
[C6]. Z. Shi*, S. Gao, J. Du, H. Ma and L. Shi, “Automatic Design of Dispatching Rules for Real-Time Optimization of Complex Production Systems”, Proceedings of the 2019 IEEE/SICE International Symposium on System Integrations, pp. 55-60, 2018, 10.1109/SII.2019.8700391.
[C5]. Z. Shi, Z. Huang and L. Shi, “Two-stage Flow Shop with a Batch Processor and Limited Buffer”, Proceedings of the 2016 IEEE Conference on Automation Science and Engineering, pp. 395-400, 2016, 10.1109/COASE.2016.7743432.
[C4]. Z. Shi, P. Liu, H. Gao and L. Shi, “Production Planning for a Class of Batch Processing Problem”, Proceedings of the 2015 IEEE Conference on Automation Science and Engineering, pp. 1188-1193, 2015, 10.1109/CoASE.2015.7294259.
[C3]. Z. Shi, L. Wang and L. Shi, “Approximation Method to Rank-One Binary Matrix Factorization”, Proceedings of the 2014 IEEE Conference on Automation Science and Engineering, pp. 800-805, 2014, 10.1109/CoASE.2014.6899417.
[C2]. B. Sun, Z. Shi, J. Song, G. Zhu and L. Shi, “A Linearized Model and Nested Partitions Heuristics for VMAT Radiation Treatment Planning Optimization”, Proceedings of the 2013 IEEE Conference on Automation Science and Engineering, pp. 629-633, 2013, 10.1109/CoASE.2013.6654068.
[C1]. L. Wang, Z. Shi and L. Shi, “A Novel Quadratic Formulation for Customer Order Scheduling Problem”, Proceedings of the 2013 IEEE Conference on Automation Science and Engineering, pp. 576-580, 2013, 10.1109/CoASE.2013.6654049.