1. Problem Solving with Mathematical Models.

2. Deterministic Optimization Models in Operations Research.

3. Improving Search.

4. Linear Programming Models.

5. Simplex Search for Linear Programming.

6. Interior Point Methods for Linear Programming.

7. Duality and Sensitivity in Linear Programming.

8. Multiobjective Optimization and Goal Programming.

9. Shortest Path and Discrete Dynamic Programming.

10. Network Flows.

11. Discrete Optimization Models.

12. Discrete Optimization Methods.

13. Unconstrained Nonlinear Programming.

14. Constrained Nonlinear Programming.