Discrete Optimization: Definitions

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Related lectures (32)

Page 3 of 4

Semi-Definite Programming

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

Optimization and Simulation

Explores greedy heuristics in optimization, integrality constraints, and comparison of optimization methods.

Linear Programming Basics

Covers deriving basic linear program representation, finding solutions, and exploring optimality.

Solving Linear Programs: SIMPLEX Method

Explains the SIMPLEX method for solving linear programs and optimizing the solution through basis variable manipulation.

Simplex Algorithm: Exercises & Interpretation

Covers exercises on the Simplex Algorithm, optimizing solutions subject to linear constraints.

Simplex Algorithm: Tableau

Covers the main idea behind the Simplex algorithm and explains the Tableau method for solving linear programming problems.

Branch & Bound: Optimization

Covers the Branch & Bound algorithm for efficient exploration of feasible solutions and discusses LP relaxation, portfolio optimization, Nonlinear Programming, and various optimization problems.

Optimization: Classical Problems

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

Optimal Decision Making: Exercises & Solutions

Covers exercises and solutions in translating text problems into linear programming and optimizing decision-making processes.

Simplex Algorithm: Basics

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