Introduction to Operations Research
2024 Release
by Frederick S. Hillier
Publisher: McGraw-Hill Higher Education
Book Details
| Print ISBN | 9781264856961 |
| eText ISBN | 9781260586930 |
| Publisher | McGraw-Hill Higher Education |
| Publishing Year | 2021 |
| Language | English |
Introduction to Operations Research: 2024 Release is a textbook published by McGraw-Hill Higher Education that presents foundational methods in operations research. The volume introduces how analytics and operations research professionals analyze problems, linking quantitative modeling to expanded business applications.
Core coverage focuses on mathematical optimization techniques and probabilistic modeling frameworks. The text introduces foundational approaches such as linear programming alongside stochastic models, decision analysis, and computer simulation.
A co-author received the INFORMS Expository Writing Award for the work. Designed to support student learning, the material incorporates intuitive explanations, professional practice examples, and state-of-the-art software tools, conveying mathematical developments in plain language without excessive mathematics.
Table of Contents
Chapter 1: Introduction
Chapter 2: Overview of How Operations Research and Analytics Professionals Analyze Problems
Chapter 3: Introduction to Linear Programming
Chapter 4: Solving Linear Programming Problems: The Simplex Method
Chapter 5: The Theory of the Simplex Method
Chapter 6: Duality Theory
Chapter 7: Linear Programming under Uncertainty
Chapter 8: Other Algorithms for Linear Programming
Chapter 9: The Transportation and Assignment Problems
Chapter 10: Network Optimization Models
Chapter 11: Dynamic Programming
Chapter 12: Integer Programming
Chapter 13: Nonlinear Programming
Chapter 14: Metaheuristics
Chapter 15: Game Theory
Chapter 16: Decision Analysis
Chapter 17: Queueing Theory
Chapter 18: Inventory Theory
Chapter 19: Markov Decision Processes
Chapter 20: Simulation
Chapter Appendix 1: Documentation for the OR Courseware
Chapter Appendix 2: Convexity
Chapter Appendix 3: Classical Optimization Methods
Chapter Appendix 4: Matrices and Matrix Operations
Chapter Appendix 5: Table for a Normal Distribution
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