Exact Methods for Integer Optimization

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Optimal Decision Making: Sensitivity Analysis

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

Optimization Problems: Path Finding and Portfolio Allocation

Covers optimization problems in path finding and portfolio allocation.

Introduction to Optimization

Covers the basics of optimization, including historical perspectives, mathematical formulations, and practical applications in decision-making problems.

Semi-Definite Programming

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

Optimal Decision Making: Exercises & Solutions

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

Nonlinear Optimization Methods

Covers methods for solving nonlinear optimization problems, including direct search, Newton-Raphson, and branch and bound.

Branch and Bound: Optimization Techniques

Covers the Branch and Bound optimization technique with LP Relaxation and Integral Optimal Solutions.

Discrete optimization: Knapsack

Explores modeling classic optimization problems as mixed integer linear problems, focusing on the knapsack problem and its applications.

Branch and Bound: Heuristic Maximization

Explains the Branch and Bound algorithm for heuristic maximization problems using LP relaxations and pruning techniques.

Discrete Optimization: Definitions

Covers definitions and concepts in discrete optimization, including binary linear problems and combinatorial optimization.