Course taught during fall 2018 and 2019.
The course is completely based on the excerpts of a few textbooks Bernard Kolman and Robert E. Beck, Elementary Linear Programming with Applications and Convex Optimization by Stephen Boyd. The key components of this course include
- Review of System of Linear Equations
- Several variants of Least Square solutions
- Least Square Solutions with Constraints
- Adaptive solutions (LMS and RLS)
- Linear Programing (Duality, Slackness Theorem)
- KKT Conditions
- Non-Linear Programming (Integer , Cone and Semi-Definite Programming)
- Optimization of Convex functions
- Meta Heuristic Optimization (Particle Swarm Optimization)
- Meta Heuristic Optimization (Genetic Algorithms)
- Meta Heuristic Optimization (Ant Colony Optimization)
Course Materials
Exercise Sheets