| Inverse optimization: Closed-form solutions, geometry, and goodness of fit TCY Chan, T Lee, D Terekhov Management Science 65 (3), 1115-1135, 2019 | 94 | 2019 |
| Robust inverse optimization K Ghobadi, T Lee, H Mahmoudzadeh, D Terekhov Operations Research Letters 46 (3), 339-344, 2018 | 43 | 2018 |
| Integrating queueing theory and scheduling for dynamic scheduling problems D Terekhov, TT Tran, DG Down, JC Beck Journal of Artificial Intelligence Research 50, 535-572, 2014 | 36 | 2014 |
| Queueing-theoretic approaches for dynamic scheduling: A survey D Terekhov, DG Down, JC Beck Surveys in Operations Research and Management Science 19 (2), 105-129, 2014 | 35 | 2014 |
| An ensemble learning framework for model fitting and evaluation in inverse linear optimization A Babier, TCY Chan, T Lee, R Mahmood, D Terekhov Informs Journal on Optimization, ijoo. 2019.0045, 2021 | 34 | 2021 |
| An extended queueing control model for facilities with front room and back room operations and mixed-skilled workers D Terekhov, JC Beck European Journal of Operational Research 198 (1), 223-231, 2009 | 28 | 2009 |
| Solving two-machine assembly scheduling problems with inventory constraints D Terekhov, MK Doğru, U Özen, JC Beck Computers & Industrial Engineering 63 (1), 120-134, 2012 | 27 | 2012 |
| A constraint programming approach for solving a queueing design and control problem D Terekhov, JC Beck, KN Brown INFORMS Journal on Computing 21 (4), 549-561, 2009 | 27 | 2009 |
| A robust optimization model for tactical capacity planning in an outpatient setting N Aslani, O Kuzgunkaya, N Vidyarthi, D Terekhov Health Care Management Science 24, 26-40, 2021 | 26 | 2021 |
| Learning linear programs from optimal decisions Y Tan, D Terekhov, A Delong Advances in Neural Information Processing Systems 33, 2020 | 26 | 2020 |
| Deep inverse optimization Y Tan, A Delong, D Terekhov International Conference on Integration of Constraint Programming …, 2019 | 24 | 2019 |
| Solving a stochastic queueing design and control problem with constraint programming D Terekhov, JC Beck, KN Brown PROCEEDINGS OF THE NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE 22 (1), 261, 2007 | 18 | 2007 |
| Long-run stability in dynamic scheduling D Terekhov, T Tran, D Down, JC Beck Proceedings of the International Conference on Automated Planning and …, 2012 | 12 | 2012 |
| A constraint programming approach for solving a queueing control problem D Terekhov, JC Beck Journal of Artificial Intelligence Research 32, 123-167, 2008 | 11 | 2008 |
| Inverse integer optimization with an imperfect observation M Moghaddass, D Terekhov Operations Research Letters 48 (6), 763-769, 2020 | 10 | 2020 |
| Investigating two-machine dynamic flow shops based on queueing and scheduling D Terekhov, TT Tran, JC Beck Proceedings of ICAPS’10 Workshop on Planning and Scheduling Under Uncertainty, 2010 | 9 | 2010 |
| Comparing Inverse Optimization and Machine Learning Methods for Imputing a Convex Objective Function EH Iraj, D Terekhov arXiv preprint arXiv:2102.10742, 2021 | 7 | 2021 |
| Logic-based Benders decomposition for two-stage flexible flow shop scheduling with unrelated parallel machines Y Tan, D Terekhov Advances in Artificial Intelligence: 31st Canadian Conference on Artificial …, 2018 | 7 | 2018 |
| A Case-Based Undergraduate Operations Research Course DM Frances, D Terekhov INFORMS Transactions on Education 19 (2), 67-80, 2019 | 6 | 2019 |
| Hybrid queueing theory and scheduling models for dynamic environments with sequence-dependent setup times TT Tran, D Terekhov, DG Down, JC Beck Twenty-Third International Conference on Automated Planning and Scheduling, 2013 | 6 | 2013 |
J. Christopher BeckProfessor of Mechanical and Industrial Engineering, University of Toronto在 mie.utoronto.ca 的电子邮件经过验证
