Covers the basics of linear programming, defining corners, extreme points, and feasible solutions within polyhedrons.
Covers optimization algorithms, convergence properties, and time complexity of sequences and functions.
Introduces linear programming basics, including optimization problems, cost functions, simplex algorithm, geometry of linear programs, extreme points, and degeneracy.
Covers the concept of hedging for Linear Programs and the simplex method, focusing on minimizing costs and finding optimal solutions.
Explores relations between events, disjunctive constraints, and modeling with binary variables in optimization problems.
Explores optimization in energy system modeling, covering decision variables, objective functions, and different strategies with their pros and cons.
