Primal-dual Optimization

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Explores primal-dual optimization, conjugation of functions, strong duality, and quadratic penalty methods in data mathematics.

Explains the process of finding an initial Basic Feasible Solution for linear optimization problems using the Simplex Algorithm.

Explores primal-dual optimization, minimax problems, and gradient descent-ascent methods for optimization algorithms.

Covers optimality conditions, strong duality, and complementarity slackness in linear optimization.

Explores the concept of duality in linear programming, discussing the relationship between primal and dual problems.

Explores the formulation of the auxiliary problem in linear optimization and its role in optimal decision-making.

Explores Linear Programming Duality, covering weak duality, strong duality, Lagrange multipliers interpretation, and optimization constraints.

Covers linear programming duality and complementary slackness condition.

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

Covers optimization problems in path finding and portfolio allocation.