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Optimal Planning and Scheduling

Activities of MACC in planning and scheduling are strongly oriented toward industrial applications, through which we have made advances in novel formulations and computational strategies. This includes optimal scheduling of furnace and converter operation in a nickel smelting plant, optimal production scheduling in a food manufacturing operation, and optimal scheduling of hydropower generation systems. The hydropower scheduling application includes consideration of uncertainty in electricity prices, inflows and plant parameters, for which stochastic programming and model-based feedback control strategies have been developed. Applications of planning under include optimal raw material purchase planning under uncertainty in primary steelmaking, and multiperiod refinery planning. The above studies have involved collaboration with five industrial partners, leading in several cases to in-house adoption of the approaches within the company.

Dr. Chris L. E. Swartz
Professor and Director, MACC
Dr. Thomas E. Marlin
Professor Emeritus
Ariel Boucheikhchoukh
M.A.Sc. Candidate
Pedro Castillo
Ph.D. Candidate
Mahir Jalanko
Ph.D. Candidate
Pulkit Mathur
Ph.D. Candidate
Inventory Pinch Based Algorithm for Gasoline Blend Planning with Uncertainty in Components Qualities
Computer Aided Chemical Engineering, 44 1525-1530 (2018)  -  [ Publisher Version ]
Optimal Short-Term Scheduling for Cascaded Hydroelectric Power Systems considering Variations in Electricity Prices
Mathur, P.Swartz, C. L. E., Zyngier, D., Welt, F.
Computer Aided Chemical Engineering, 44 1345-1350 (2018)
Supply-demand pinch based methodology for multi-period planning under uncertainty in components qualities with application to gasoline blend planning
Computers & Chemical Engineering, 119 425-438 (2018)  -  [ Publisher Version ]
An optimization framework for scheduling of converter aisle operation in a nickel smelting plant
Computers & Chemical Engineering, 119 195-214 (2018)  -  [ Publisher Version ]
Impact of crude distillation unit model accuracy on refinery production planning
Frontiers of Engineering Management, 5 (2) 195-201 (2018)  -  [ Publisher Version ]
Supply-Demand Based Algorithm for Gasoline Blend Planning Under Time-Varying Uncertainty in Demand
International Conference on Applied Physics, System Science and Computers, 183-189 (2018)  -  [ Publisher Version ]
A dynamic game theoretic framework for process plant competitive upgrade and production planning
AIChE Journal, 64 (3) 916-925 (2017)  -  [ Publisher Version ]
Global Optimization of Nonlinear Blend-Scheduling Problems
Castillo, P., Pedro M. Castro, Mahalec, V.
Engineering, 3 (2) 188-201 (2017)  -  [ Publisher Version ]
Global Optimization Algorithm for Large-Scale Refinery Planning Models with Bilinear Terms
Castillo, P., Pedro M. Castro, Mahalec, V.
Industrial & Engineering Chemistry Research, 56 (2) 530-548 (2017)  -  [ Publisher Version ]
Globally optimal nonlinear model predictive control based on multi-parametric disaggregation
Xiaoqiang Wang, Mahalec, V., Feng Qian
Journal of Process Control, 52 1-13 (2017)  -  [ Publisher Version ]