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Lecture
Duality in Linear Programming
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Related lectures (32)
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Linear Programming: Two-phase Simplex Algorithm
Covers the application of the two-phase Simplex algorithm to solve linear programming problems.
Optimization Methods: Theory Discussion
Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.
Lagrangian Duality: Theory and Applications
Explores Lagrangian duality in convex optimization, discussing strong duality, dual solutions, and practical applications in second-order cone programs.
Linear Programming Duality
Explores the concept of duality in linear programming and its practical implications in optimization.
Optimal Decision Making: Duality
Delves into duality in optimization, weak duality, cost certificates, and transforming non-linear programs into linear ones.
Duality, Constraint relaxation
Explores duality and constraint relaxation in optimization problems with practical examples.
Duality Theorems
Explores duality theorems in linear programming, emphasizing optimal solutions and degeneracies.
Optimality Conditions in Linear Optimization
Covers optimality conditions, strong duality, and complementarity slackness in linear optimization.
Weak and Strong Duality
Covers weak and strong duality in optimization problems, focusing on Lagrange multipliers and KKT conditions.
Lagrangian Duality: Convex Optimization
Explores Lagrangian duality in convex optimization, transforming problems into min-max formulations and discussing the significance of dual solutions.
