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Lecture
Nonlinear Programming: Part I
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Related lectures (30)
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Optimization Methods: Theory Discussion
Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.
Optimal Decision Making: Sensitivity Analysis
Covers sensitivity analysis in linear programming, focusing on optimal solutions and their sensitivities to changes.
Linear Programming: Weighted Bipartite Matching
Covers linear programming, weighted bipartite matching, and vertex cover problems in optimization.
Optimization Problems: Path Finding and Portfolio Allocation
Covers optimization problems in path finding and portfolio allocation.
Optimisation in Energy Systems
Explores optimization in energy system modeling, covering decision variables, objective functions, and different strategies with their pros and cons.
KKT and Convex Optimization
Covers the KKT conditions and convex optimization, discussing constraint qualifications and tangent cones of convex sets.
Optimisation with Constraints: Interior Point Algorithm
Explores optimization with constraints using KKT conditions and interior point algorithm on two examples of quadratic programming.
Convex Optimization Tutorial: KKT Conditions
Explores KKT conditions in convex optimization, covering dual problems, logarithmic constraints, least squares, matrix functions, and suboptimality of covering ellipsoids.
Optimization with Constraints: KKT Conditions
Covers the KKT conditions for optimization with constraints, essential for solving constrained optimization problems efficiently.
Convex Optimization Problems: Theory and Applications
Explores convex optimization problems, optimality criteria, equivalent problems, and practical applications in transportation and robotics.
