Process Optimization (CHE 521)
An introduction to chemical process optimization. Model development and classification of optimization problems. Linear programming techniques, simplex algorithm, barrier method, parametric sensitivity analysis and duality theory. Convex optimization, necessary and sufficient conditions for optimality for unconstrained and constrained problems. Mixed-integer programming. Trajectory optimization. Applications include optimization of heat exchanger networks, multistage separation processes, batch operations, process scheduling and chemical reactor networks.
Introduction to Process Control (CHE 341)
Laplace transform techniques. Proportional-integral-derivative control. Frequency response methods. Stability analysis. Controller tuning. Process control simulation and computer control systems. Process identification.
Short Courses on Julia and InfiniteOpt.jl
In this short course, I provide a hands-on introduction to:
- programming in Julia,
- solving optimization problems via JuMP.jl, and
- modeling infinite-dimensional optimization problems in InfiniteOpt.jl.
The course materials are freely available here on GitHub. By the end of this course, students should be familiar with:
- scripting in Julia,
- solving optimization problems in JuMP.jl and InfiniteOpt.jl,
- and should have the resources they need to learn further.
To date, I have taught this course at the University of Wisconsin-Madison, Carnegie Mellon University, Busan South Korea, Toronto Canada, and in the University of Waterloo.