1 Introduction2 Overview of the Operations Research Modeling Approach3 Introduction to Linear Programming4 Solving Linear Programming Problems: The Simplex Method5 The Theory of the Simplex Method6 Duality Theory and Sensitivity Analysis7 Other Algorithms for Linear Programming8 The Transportation and Assignment Problems9 Network Optimization Models 10 Dynamic Programming11 Integer Programming12 Nonlinear Programming13 Metaheuristics14 Game Theory15 Decision Analysis16 Markov Chains17 Queueing Theory18 Inventory Theory19 Markov Decision Processes20 SimulationAppendix 1 Documentation for the OR CoursewareAppendix 2 ConvexityAppendix 3 Classical Optimization MethodsAppendix 4 Matrices and Matrix OperationsAppendix 5 Table for a Normal DistributionSupplements on the Online Learning CenterAdditional CasesSupplement to Appendix 3.1 More about LINGOSupplement to Chapter 7 Linear Goal Programming and Its Solution ProceduresSupplement to Chapter 8 A Case Study with Many Transportation ProblemsSupplement 1 to Chapter 18 Derivation of the Optimal Policy for the Stochastic Single-Period Model for Perishable ProductsSupplement 2 to Chapter 18 Stochastic Periodic-Review ModelsSupplement 1 to Chapter 20 Variance-Reducing TechniquesSupplement 2 to Chapter 20 Regenerative Method of Statistical Analysis21 The Art of Modeling with Spreadsheets22 Project Management with PERT/CPM23 Additional Special Types of Linear Programming Problems24 Probability Theory25 Reliability26 The Application of Queueing Theory27 Forecasting28 Examples of Performing Simulations on Spreadsheets with Crystal BallAppendix 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. The 6th edition won honorable mention for the 1995 Lanchester Prize (best English-language publication of any kind in the field) and Dr. Hillier also was awarded the 2004 INFORMS Expository Writing Award for the 8th edition. His other books include The Evaluation of Risky Interrelated Investments, Queueing Tables and Graphs, Introduction to Stochastic Models in Operations Research, and Introduction to Mathematical Programming. He received his BS in industrial engineering and doctorate specializing in operations research and management science from Stanford University. The winner of many awards in high school and college for writing, mathematics, debate, and music, he ranked first in his undergraduate engineering class and was awarded three national fellowships (National Science Foundation, Tau Beta Pi, and Danforth) for graduate study. Dr. Hilliers research has extended into a variety of areas, including integer programming, queueing theory and its application, statistical quality control, and production and operations management. He also has won a major prize for research in capital budgeting.