Introduction to Operations Research ISE

1) Introduction

2) Overview of How Operations Research and Analytics Professionals Analyze Problems

3) Introduction to Linear Programming

4) Solving Linear Programming Problems: The Simplex Method

5) The Theory of the Simplex Method

6) Duality Theory

7) Linear Programming under Uncertainty

8) Other Algorithms for Linear Programming

9) The Transportation and Assignment Problems

10) Network Optimization Models

11) Dynamic Programming

12) Integer Programming

13) Nonlinear Programming

14) Metaheuristics

15) Game Theory

16) Decision Analysis

17) Queueing Theory

18) Inventory Theory

19) Markov Decision Processes

20) Simulation

Appendix 1 - Documentation for the OR Courseware

Appendix 2 - Convexity

Appendix 3 - Classical Optimization Methods

Appendix 4 - Matrices and Matrix Operations

Appendix 5 - Table for a Normal Distribution

For over four decades, Introduction to Operations Research has been the classic text on operations research. While building on the classic strengths of the text, the author continues to find new ways to make the text current and relevant to students. One way is by incorporating a wealth of state-of-the art, user-friendly software and more coverage of business applications than ever before. When the first co-author received the prestigious Expository Writing Award from INFORMS for a recent edition, the award citation described the reasons for the book’s great success as follows:

“Two features account for this success. First, the editions have been outstanding from students’ points of view due to excellent motivation, clear and intuitive explanations, good examples of professional practice, excellent organization of material, very useful supporting software, and appropriate but not excessive mathematics. Second, the editions have been attractive from instructors’ points of view because they repeatedly infuse state-of-the-art material with remarkable lucidity and plain language.”