| Scope for industrial applications of production scheduling models and solution methods I Harjunkoski, CT Maravelias, P Bongers, PM Castro, S Engell, ... Computers & Chemical Engineering 62, 161-193, 2014 | 630 | 2014 |
| Risk management for a global supply chain planning under uncertainty: models and algorithms F You, JM Wassick, IE Grossmann AIChE Journal 55 (4), 931-946, 2009 | 314 | 2009 |
| A distributed ledger for supply chain physical distribution visibility H Wu, Z Li, B King, Z Ben Miled, J Wassick, J Tazelaar Information 8 (4), 137, 2017 | 287 | 2017 |
| Model predictive controller JM Wassick, PS McCroskey, JJ McDonough, DK Steckler US Patent 6,056,781, 2000 | 192 | 2000 |
| A deep reinforcement learning approach for chemical production scheduling CD Hubbs, C Li, NV Sahinidis, IE Grossmann, JM Wassick Computers & Chemical Engineering 141, 106982, 2020 | 180 | 2020 |
| Sustainable supply chain optimisation: An industrial case study Q Zhang, N Shah, J Wassick, R Helling, P Van Egerschot Computers & Industrial Engineering 74, 68-83, 2014 | 169 | 2014 |
| Model predictive controller JM Wassick, PS McCroskey, JJ McDonough, DK Steckler US Patent 5,740,033, 1998 | 157 | 1998 |
| Integrated planning and scheduling under production uncertainties: Bi-level model formulation and hybrid solution method Y Chu, F You, JM Wassick, A Agarwal Computers & Chemical Engineering 72, 255-272, 2015 | 149 | 2015 |
| From rescheduling to online scheduling D Gupta, CT Maravelias, JM Wassick Chemical Engineering Research and Design 116, 83-97, 2016 | 127 | 2016 |
| Integrated scheduling and dynamic optimization of batch processes using state equipment networks Y Nie, LT Biegler, JM Wassick AIChE Journal 58 (11), 3416-3432, 2012 | 124 | 2012 |
| Enterprise-wide optimization in an integrated chemical complex JM Wassick Computers & Chemical Engineering 33 (12), 1950-1963, 2009 | 120 | 2009 |
| Discrete time formulation for the integration of scheduling and dynamic optimization Y Nie, LT Biegler, CM Villa, JM Wassick Industrial & Engineering Chemistry Research 54 (16), 4303-4315, 2015 | 109 | 2015 |
| Simulation-based optimization framework for multi-echelon inventory systems under uncertainty Y Chu, F You, JM Wassick, A Agarwal Computers & Chemical Engineering 73, 1-16, 2015 | 109 | 2015 |
| Or-gym: A reinforcement learning library for operations research problems CD Hubbs, HD Perez, O Sarwar, NV Sahinidis, IE Grossmann, ... arXiv preprint arXiv:2008.06319, 2020 | 101 | 2020 |
| Design of resilient supply chains with risk of facility disruptions P Garcia-Herreros, JM Wassick, IE Grossmann Industrial & Engineering Chemistry Research 53 (44), 17240-17251, 2014 | 99 | 2014 |
| Data-driven individual and joint chance-constrained optimization via kernel smoothing BA Calfa, IE Grossmann, A Agarwal, SJ Bury, JM Wassick Computers & Chemical Engineering 78, 51-69, 2015 | 86 | 2015 |
| Addressing the operational challenges in the development, manufacture, and supply of advanced materials and performance products JM Wassick, A Agarwal, N Akiya, J Ferrio, S Bury, F You Computers & Chemical Engineering 47, 157-169, 2012 | 85 | 2012 |
| Chemical supply chain network optimization J Ferrio, J Wassick Computers & Chemical Engineering 32 (11), 2481-2504, 2008 | 80 | 2008 |
| Multisite capacity, production, and distribution planning with reactor modifications: MILP model, bilevel decomposition algorithm versus Lagrangean decomposition scheme F You, IE Grossmann, JM Wassick Industrial & Engineering Chemistry Research 50 (9), 4831-4849, 2011 | 79 | 2011 |
| A hybrid blockchain ledger for supply chain visibility Z Li, H Wu, B King, ZB Miled, J Wassick, J Tazelaar 2018 17th International Symposium on Parallel and Distributed Computing …, 2018 | 65 | 2018 |
