Solving Linear Programs: SIMPLEX Method

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Covers optimization problems in path finding and portfolio allocation.

Covers the basics of linear programming and the simplex method, focusing on finding optimal solutions and handling degeneracy.

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

Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.

Introduces the Simplex algorithm for solving flow problems and handling negative cost cycles.

Covers semi-definite programming and optimization over positive semidefinite cones.

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

Explores finding the initial Basic Feasible Solution (BFS) in a linear program.

Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.

Covers the basics of linear optimization, including equations, polyhedrons, feasible directions, and optimal solutions.