ISBN 9780071333467,Introduction To Operations Research

Introduction To Operations Research



Tata McGraw - Hill Education

Publication Year 2011

ISBN 9780071333467

ISBN-10 0071333460


Edition 9th
Number of Pages 1132 Pages
Language (English)

Science fiction

Introduction To Operations Research by Gerald J. Lieberman, Bodhibrata Nag, Frederick S. Hillier, Preetam Basu is a text for students that will help them understand the latest development within the Operations Research. This book deals with the technologies and the software required in order to create successful business application models that are adopted by companies in order to ensure success. This book contains an introductory chapter, a chapter on Overview of the Operations Research Modeling Approach, The Theory of the Simplex Method, Nonlinear Programming, Integer Programming as well as Dynamic Programming. It also deals with Solving Linear Programming Problems: The Simplex Method, Network Optimization Models and Other Algorithms for Linear Programming. There are other chapters such as Introduction to Linear Programming, The Transportation and Assignment Problems, and Duality Theory and Sensitivity Analysis. The authors also deal with Metaheuristics, Decision Analysis, Game Theory, Markov Decision Processes, Inventory Theory, Queueing Theory and Markov Chains Simulation. This book contains a glossary of terms which students will find highly useful. There are also new additions made such as preparing excel sheets for presentation purposes. This is a text that has been used by students and professionals for the purpose of understanding Operations Research. About The Authors Gerald J. Lieberman was a professor at Stanford University. His expertise includes operations research and statistics. His published works included Introduction To Operations Research, Engineering Statistics, Tables of the Hypergeometric Probability Distribution and Introduction to Management Science: A Modeling And Case Studies Approach With Spreadsheets. He was a well-reputed researcher and scholar who published several research papers on Operations Research. These are cited today by modern academics in order to better explain the fundamentals of these field. He passed away in the year 1999. Bodhibrata Nag is an associate Professor at the Indian Institute of Management, Kolkata. He has also worked as a Deputy Chief Engineer for the South Eastern Railways. He has a B.Tech degree from IIT Madras in Electrical Engineering and Doctorate degree in Operations Research and Systems Analysis from IIM Calcutta. Frederick S. Hillier is an award-winning mathematician and writer. He has written extensively about mathematics, engineering and even social sciences. His published works include Introduction to Operations Research, The Evaluation of Risky Interrelated Investments, Introduction to Programming, Introduction to Management Science: A Modeling and Case Studies Approach with Spreadsheets and Introduction to Stochastic Models in Operations Research. He has won the Hamilton Award for his contribution in the field of engineering. He also won three fellowships and graduated from Stanford, majoring in Operations Research. He has been associated with Cornell, University of Canterbury, Carnegie-Mellon University and the Technical University of Denmark. He was part of the Stanford Engineering department for over three decades. Preetam Basu is a Professor at IIM, Kolkata. He is best known for his co-written work Introduction To Operations Research. He has also published Analysis of Back-Office Outsourcing Contracts for Financial Services Operations in the Journal of Operational Research Society. He was associated with the University of Connecticut as a Teaching and Research Assistant at the Operations and Information Management Department. His interests include Services Operations, Working Capital Management and Operations Research Management. TABLE OF CONTENTS Chapter 1. Introduction Chapter 2. Overview of the Operations Research Modeling Approach 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 and Sensitivity Analysis Chapter 7. Other Algorithms for Linear Programming Chapter 8. The Transportation and Assignment Problems Chapter 9. Network Optimization Models Chapter 10. Dynamic Programming Chapter 11. Integer Programming Chapter 12. Nonlinear Programming Chapter 13. Meta-heuristics Chapter 14. Game Theory Chapter 15. Decision Analysis Chapter 16. Markov Chains Chapter 17. Queueing Theory Chapter 18. Inventory Theory Chapter 19. Markov Decision Processes Chapter 20. Simulation