Covers line search, Newton's method, BFGS, and conjugate gradient in nonlinear optimization.
Introduces linear programming basics, including optimization problems, cost functions, simplex algorithm, geometry of linear programs, extreme points, and degeneracy.
Explores optimization in energy systems, focusing on decision-making through objective functions and constraints to determine system states.
Covers the concept of hedging for Linear Programs and the simplex method, focusing on minimizing costs and finding optimal solutions.
Explores finding the initial Basic Feasible Solution (BFS) in a linear program.
