Optimization Course Schedule
| Week | Topic | Reading | HW/Projects |
|---|---|---|---|
| 1 | Introduction to Optimization | Ch 1 | Optimization Basics and Optimize with Python |
| 2 | Modeling Concepts | Ch 2 | Two Bar Truss |
| 3 | Modeling Concepts | Ch 2 | Spring Design |
| 4 | Unconstrained Optimization | Ch 3 | Heat Integration or Slurry Pipeline (your choice) |
| 5 | Unconstrained Optimization | Ch 3 | Quiz #1 |
| 6 | Unconstrained Optimization | Ch 3 | Project #1 |
| 7 | Discrete Optimization | Ch 4 | Search Directions |
| 8 | Discrete Optimization | Ch 4 | Discrete Design |
| 9 | Genetic Algorithms | Ch 5 | Simulated Annealing |
| 10 | KKT Equations | Ch 6 | Mid-Term Exam |
| 11 | Constrained Algorithms | Ch 7 | KKT Conditions |
| 12 | Constrained Algorithms | Ch 7 | Interior Point Method |
| 13 | Robust Design | Ch 8 | Dynamic Estimation |
| 14 | Dynamic Optimization | Ch 9 | Quiz |
| 15 | Presentations | Project #2 | |
| Final Exam |
- Schedule subject to change
