| Optimization Modeling (Modules A - C) |
| Focus on modeling and algorithms with applications to process optimization, process synthesis and molecular design |
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June 12
Thursday |
Module A: Nonlinear Programming
Lorenz Biegler |
| 8:30 to 10:00 AM |
- Nonlinear Programming
- Unconstrained Newton-type Methods
- Karush Kuhn Tucker Conditions
- Linear Programming, Quadratic Programming
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| 10:15 to Noon |
- Nonlinear Programming Algorithms
- Successive Quadratic Programming
- Interior Point/Barrier Methods (IPOPT)
- Reduced Gradient Methods (MINOS, CONOPT)
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| 1:00 to 3:15 PM |
- Process Optimization
- Flowsheet Optimization for Design
- Real-time Optimization
- Sensitivity of Optimal Solutions
- Multiperiod Optimization for Uncertainty
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| 3:30 to 5:30 PM |
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June 13
Friday |
Module B: Mixed Integer and Disjunctive Programming
Ignacio Grossmann |
| 8:30 to 10:00 AM |
- Mixed-integer Linear Programming
- Major Types Integer and Mixed-integer Constraints
- Algorithms: Branch and Bound
- Example: Synthesis Separation Network
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| 10:15 to 11:45 AM |
- Logic Based Optimization and Disjunctive Programming
- Propositional Logic for Formulating Constraints
- Examples of Logic Constraints
- Convex Hull and Big-M Reformulations
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| 1:00 to 2:15 PM |
- Mixed-integer Nonlinear Programming
- Branch and Bound, Outer-approximation, Benders Decomposition, Extended Cutting Plane
- DICOPT: Examples Parameter Estimation, Synthesis Heat Exchanger Networks
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| 2:30 to 3:45 PM |
- Generalized Disjunctive Programming
- Logic-based Methods and Reformulation (LOGMIP)
- Examples: Distillation Columns, Sequences
- Flowsheet Synthesis
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| 4:00 to 6:00 PM |
- Practice Session of Mixed-integer Modeling
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June 14
Saturday |
Module C: Global Optimization and Optimization Under Uncertainty
Nick Sahinidis |
| 8:30 to 10:00 AM |
- Applications of global optimization
- Building blocks of global optimization algorithms
- Branch and bound algorithms for global NLP and MINLP
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| 10:15 to Noon |
- Separable and factorable programming techniques
- Range reduction techniques
- Branch and Reduce algorithm (BARON)
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| 1:00 to 3:15 PM |
- Stochastic linear programming
- Decomposition and sampling algorithms
- Stochastic integer programming
- Planning the supply chain under uncertainty
- Probabilistic and fuzzy programming
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| 3:30 to 5:30 PM |
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| Integrated Process Operations (Modules D-F) |
| Focus on three major decision levels in plant and enterprise-wide optimization |
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June 16
Monday |
Module D: Mixed-integer Models for Planning and Scheduling
Ignacio Grossmann |
| 8:30 to 10:00 AM |
- Introduction and Roadmap to Scheduling Problems
- Overview Mathematical Programming Models
- Batch Scheduling: Single Stage, Parallel Units
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| 10:15 to Noon |
- Batch Scheduling: Multi-stage Plants
- Flowshop Scheduling
- State-task and Resource-task Network
- Discrete and Continuous Time Models
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| 1:00 to 2:15 PM |
- Scheduling of Continuous Multistage Plants
- Refinery Scheduling and Blending
- Multi-site Production Planning
- Supply Chain Models
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| 2:30 to 3:45 PM |
- Constraint Programming
- Hybrid Methods for Scheduling: Single Stage and STN
- Decomposition Methods for Planning and Scheduling: Lagrangean and Bi-level Methods
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| 3:30 to 5:00 PM |
- Practice Session Modeling Scheduling Problems
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June 17
Tuesday |
Module E: Process Dynamics and Control
Erik Ydstie |
| 8:30 to 10:00 AM |
- Process modeling using conservation laws
- The state representations and the second law of thermodynamics
- Lumped models of simple systems
- Examples: Carbothermic reduction of alumina
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| 10:15 to 11:45 AM |
- Process networks
- Modeling a complete plant using networks
- Supply chain networks
- Business networks
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| 1:00 to 2:15 PM |
- Inventory control of process systems
- Flow control in network
- Particulate systems
- Examples: Solar grade Silicon and Integrated Gasification Combine Cycle power plants
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| 2:30 to 3:45 PM |
- Distributed parameter systems
- Structural properties and model development
- Fluid flow control systems
- Examples: Glass furnace
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| 4:00 to 6:00 PM |
- Practice Session: Application of process control
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June 18
Tuesday |
Module F: Differential / Algebraic Models for Real Time Optimization
Lorenz Biegler |
| 8:30 to 10:00 AM |
- Differential Algebraic Optimization
- Sequential Methods Based on ODE Solvers
- Optimal Control Methods
- Case Studies and Examples
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| 10:15 to Noon |
- Optimization of Dynamic Systems
- Collocation-based Methods
- Optimal Control and High Index DAEs
- Batch Distillation Case Study
- Optimization of Unstable Systems
- Nonlinear Model Predictive Control
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| 1:00 to 3:15 PM |
- Parameter Estimation
- Unconstrained Levenberg-Marquardt
- Trust Region Methods
- Constrained Least Squares and SQP Variants
- Robust Least Squares and Outlier Detection
- Steady State Data Reconciliation
- Dynamic Data Reconciliation
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| 3:30 to 5:00 PM |
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