Linear Constraints: Basic Solutions

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

Covers optimization problems in path finding and portfolio allocation.

Covers the basics of linear programming, defining corners, extreme points, and feasible solutions within polyhedrons.

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

Explores the significance of vertices in optimization and outlines a method to identify them using linear algebra.

Covers the transhipment problem, optimal solutions, and total unimodularity in matrices.

Covers classical optimization problems, brute force algorithms, and integer linear optimization.

Covers linear constraints and degeneracy in polyhedrons, focusing on basic solutions and degenerate cases.

Explains linear constraints and the concept of a polyhedron in optimization problems.

Explores convex sets, their properties, and applications in optimization.