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Preface. I. MODELS AND MODELING. 1. Introduction to Modeling. 2. Spreadsheet Modeling. II. OPTIMIZATION. 3. Linear Optimization. 4. Linear Programming: Graphical Analysis. 5. LP Models: Interpreting Solver Sensitivity Report. 6. Linear Programming: Applications. 7. Integer Optimization. 8. Nonlinear Optimization. 9. Multi-Objective Decision Making and Heuristics. III. PROBABILISTIC MODELS. 10. Decision Analysis. 11. Monte Carlo Simulation. 12. Queuing. 13. Forecasting. 14. Project Management: PERT and CPM. Appendix A: Basic Concepts in Probability. Appendix B. Excel Features Useful for Modeling. Appendix C. Solver Tips and Messages. Index.
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