Feasible region

Related lectures (32)

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Covers sensitivity analysis in linear programming, focusing on optimal solutions and their sensitivities to changes.

Explores the cutset formulation for the MST Problem and Gomory Cutting Planes method.

Explores extreme points in linear programming and the role of constraints in finding optimal solutions.

Explores feasible directions in linear constraints and the conditions for feasibility.

Explores optimization problems, feasible regions, and objective functions with a focus on Lagrange multipliers and convexity.

Explores certificates, proving solution existence, constraints, and linear programming duality.

Covers exercises on the Simplex Algorithm, optimizing solutions subject to linear constraints.

Illustrates the simplex algorithm through a graphical method to find optimal solutions.

Discusses gradient descent for optimization with equality constraints and iterative convergence criteria.

Covers linear programming, weighted bipartite matching, and vertex cover problems in optimization.