Explores the cutset formulation for the MST Problem and Gomory Cutting Planes method.
Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.
Covers sensitivity analysis in linear programming, focusing on optimal solutions and their sensitivities to changes.
Covers optimization problems in path finding and portfolio allocation.
Covers linear programming, weighted bipartite matching, and vertex cover problems in optimization.
Explores solving discrete optimization problems by relaxing integrality constraints.
Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.
Explores relations between events, disjunctive constraints, and modeling with binary variables in optimization problems.
Covers the application of the two-phase Simplex algorithm to solve linear programming problems.
Covers the concept of hedging for Linear Programs and the simplex method, focusing on minimizing costs and finding optimal solutions.
