Introduction to Operations Research

1 Introduction 2 Overview of the Operations Research Modeling Approach 3 Introduction to Linear Programming 4 Solving Linear Programming Problems: The Simplex Method 5 The Theory of the Simplex Method 6 Duality Theory and Sensitivity Analysis 7 Other Algorithms for Linear Programming 8 The Transportation and Assignment Problems 9 Network Optimization Models 10 Dynamic Programming 11 Integer Programming 12 Nonlinear Programming 13 Metaheuristics 14 Game Theory 15 Decision Analysis 16 Markov Chains 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 Supplements on the Online Learning Center Additional Cases Supplement to Appendix 3.1 More about LINGO Supplement to Chapter 7 Linear Goal Programming and Its Solution Procedures Supplement to Chapter 8 A Case Study with Many Transportation Problems Supplement 1 to Chapter 18 Derivation of the Optimal Policy for the Stochastic Single-Period Model for Perishable Products Supplement 2 to Chapter 18 Stochastic Periodic-Review Models Supplement 1 to Chapter 20 Variance-Reducing Techniques Supplement 2 to Chapter 20 Regenerative Method of Statistical Analysis 21 The Art of Modeling with Spreadsheets 22 Project Management with PERT/CPM 23 Additional Special Types of Linear Programming Problems 24 Probability Theory 25 Reliability 26 The Application of Queueing Theory 27 Forecasting 28 Examples of Performing Simulations on Spreadsheets with Crystal Ball Appendix 6 Simultaneous Linear Equations

Professor emeritus of operations research at Stanford University. Dr. Hillier is especially known for his classic, award-winning text, Introduction to Operations Research, co-authored with the late Gerald J. Lieberman, which has been translated into well over a dozen languages and is currently in its 8th edition.