Covers the basics of optimization, including historical perspectives, mathematical formulations, and practical applications in decision-making problems.
Covers the basics of linear programming and the simplex method, focusing on finding optimal solutions and handling degeneracy.
Explores linear programming duality, covering constraints, variables, solutions, and the relationship between primal and dual LP.
Covers the basics of linear programming, defining corners, extreme points, and feasible solutions within polyhedrons.
