1. The science of managerial decision making; Part I. Decision Making Using Deterministic Models: 2. Introduction to linear programming models; 3. Developing model formulation skills; 4. More advanced linear decision problems; 5. Output analysis I: small changes; 6. Output analysis II: large changes; 7. Integer linear programs; Part II. Decision Making Under Uncertainty: 8. Introduction to probability models; 9. Decision making under uncertainty; 10. Decision trees; 11. Management of congested service systems; 12. Monte Carlo simulation; Appendix. An Excel primer.