Pearson Education Ltd
|Number of Pages
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.
The material is organized to suit the needs of both the beginning and the advanced student.
Emphasizes the formulation and applications aspects of OR.
Numerical examples are the main vehicle for explaining new ideas.
Each numeric example is followed by a set of in-text problems.
Chapters end with (open-ended) comprehensive problems selected from published case analysis.
The problems provide a balanced coverage of the formulation, computation, and theory of OR.
The sixth edition is practically a new book. The first 18 chapters have been completely rewritten. Mathematics coverage has been revised to start easy and gradually increase in difficulty.
Now contains over 1000 problems, a 60% increase over the fifth edition.
Includes numerous new material: Floyd's Shortest Route Algorithm, Goal Programming, Analytic Hierarchy Approach, Review of Probability, Probabilistic DP, and Simulation Modeling.
Includes updated versions of TORA software and the simulation language SIMNET II.
TABLE OF CONTENTS ; -
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.