A full listing of courses and more information can be found here. The following courses are often recommended and relevant for energy systems optimization research, and a sample progression is noted with “*”.
- *COMP SCI / E C E / I SY E 524: Introduction to Optimization
- Introduction to mathematical optimization from a modeling and solution perspective.
- *COMP SCI / I SY E/ MATH / STAT 525: Linear Programming Methods
- Real linear algebra over polyhedral cones; theorems of the alternative for matrices; formulation of linear programs; duality theory and solvability; the simplex method and related methods for efficient computer solution.
- COMP SCI / I SY E 526: Advanced Linear Programming
- Polynomial time methods for linear programming; quadratic programs and linear complementarity problems and related solution techniques; solution sets and their continuity properties.
- COMP SCI / E C E / M E 532: Matrix Methods in Machine Learning
- An introduction to machine learning that focuses on matrix methods and features real-world applications ranging from classification and clustering to denoising and data analysis.
- COMP SCI / I SY E 719: Stochastic Programming
- Stochastic programming is concerned with decision making in the presence of uncertainty, where the eventual outcome depends on a future random event. Topics include modeling uncertainty in optimization problems, risk measures, stochastic programming algorithms, approximation and sampling methods, and applications.
- COMP SCI / I SY E 723: Dynamic Programming and Associated Topics
- General and special techniques of dynamic programming are developed by means of examples. Shortest-path algorithms; deterministic equipment replacement models; resource allocation problem; traveling-salesman problem; general stochastic formulations; Markovian decision processes and more
- *COMP SCI / I SY E / MATH / STAT 726: Nonlinear Optimization I
- This course emphasizes continuous, nonlinear optimization and could be taken with only a background in mathematical analysis.
- *COMP SCI / I SY E / MATH 728: Integer Optimization
- Introduction to optimization problems over integers and survey of the theory behind the algorithms used in state-of-the-art methods for solving such problems. Special attention is given to the polyhedral formulations of these problems, and to their algebraic and geometric properties.
- COMP SCI / I SY E / MATH 730: Nonlinear Optimization II
- Theory and algorithms for nonlinearly constrained optimization; relevant geometric concepts, including tangent and normal cones, theorems of the alternative, and separation results.