Includes bibliographical references and index.

1. Overview of Operations Research. I. DETERMINISTIC MODELS. 2. Introduction to Linear Programming. 3. The Simplex Method. 4. Duality and Sensitivity Analysis. 5. Transportation Model and Its Variants. 6. Network Models. 7. Advanced Linear Programming. 8. Goal Programming. 9. Integer Linear Programming. 10. Deterministic Dynamic Programming. 11. Deterministic Inventory Models. II. PROBABILISTIC MODELS. 12. Review of Basic Probability. 13. Forecasting Models. 14. Decision Analysis and Games. 15. Probabilistic Dynamic Programming. 16. Probabilistic Inventory Models. 17. Queueing Systems. 18. Simulation Modeling. 19. Markovian Decision Process. III. NONLINEAR MODELS. 20. Classical Optimization Theory. 21. Nonlinear Programming Algorithms. Appendix A: Review of Matrix Algebra. Appendix B: Introduction to Simnet II. Appendix C: Tora and Simnet II Installation and Execution. Appendix D: Statistical Tables. Appendix E: Answers to Odd-Numbered Problems. Index.

Appropriate for a variety of junior and senior undergraduate and first year graduate courses in operations research. Among these courses are Industrial Engineering, Business Administration, Statistics, Computer Science, and Mathematics. Major revision is designed to meet the needs of beginning through advanced students with an emphasis placed on the formulation and applications aspects. Provides balanced coverage of theory, applications and computations of operations research techniques. Numerical examples are main vehicle for explaining new ideas with each numeric example followed by a set of problems. TORA and SIMNET software included in text. More than 1,000 problems.