Includes bibliographical references and index.

Chapter 1: What is Operations Research? 1.1 Operations Research Models 1.2 Solving the OR Model 1.3 Queueing and Simulation Models 1.4 Art of Modeling 1.5 More than Just Mathematics 1.6 Phases of an OR Study 1.7 About this Book Problems References Chapter 2: Modeling with Linear Programming 2.1 Two-Variable LP Model 2.2 Graphical LP Solution 2.3 Selected LP Applications 2.4 Computer Solution with Solver and AMPL Problems References Chapter 3: The Simplex Method and Sensitivity Analysis 3.1 LP Model in Equation Form 3.2 Transition from Graphical to Algebraic Solution 3.3 The Simplex Method 3.4 Artificial Starting Solution 3.5 Special Cases in the Simplex Method 3.6 Sensitivity Analysis Problems References Chapter 4: Duality and Post-Optimal Analysis 4.1 Definition of the Dual Problem4.2 Primal-Dual Relationships 4.3 Economic Interpretation of Duality 4.4 Additional Simplex Algorithms 4.5 Post-Optimal Analysis Problems References Chapter 5: Transportation Model and its Variants 5.1 Definition of the Transportation Model 5.2 Nontraditional Transportation Models 5.3 The Transportation Algorithm 5.4 The Assignment Model 5.5 The Transshipment Model Problems References Chapter 6: Network Models 6.1 Scope and Definition of Network Models 6.2 Minimal Spanning Tree Algorithm 6.3 Shortest-Route Problem 6.4 Maximal Flow Model 6.5 CPM and PERT Problems References Chapter 7: Advanced Linear Programming 7.1 Simplex Method Fundamentals 7.2 Revised Simplex Method 7.3 Bounded Variables Algorithm 7.4 Duality 7.5 Parametric Linear Programming Problems References Chapter 8: Goal Programming 8.1 A Goal Programming Formulation 8.2 Goal Programming Algorithms Problems References Chapter 9: Integer Linear Programming 9.1 Illustrative Applications 9.2 Integer Programming Algorithms9.3 Traveling Salesperson (TSP) Problem Problems References Chapter 10: Deterministic Dynamic Programming 10.1 Recursive Nature of Computations in DP 10.2 Forward and Backward Recursion 10.3 Selected DP Applications 10.4 Problem of Dimensionality Problems References Chapter 11: Deterministic Inventory Models 11.1 General Inventory Model 11.2 Role of Demand in the Development of Inventory Models 11.3 Static Economic-Order-Quantity (EOQ) Models 11.4 Dynamic EOQ Models Problems References Chapter 12: Review of Basic Probability 12.1 Laws of Probability 12.2 Random Variables and Probability Distributions 12.3 Expectation of a Random Variable 12.4 Four Common Probability Distributions 12.5 Empirical Distributions Problems References Chapter 13: Decision Analysis and Games 13.1 Decision Making under Certainty-Analytic Hierarchy Process (AHP) 13.2 Decision Making under Risk 13.3 Decision under Uncertainty 13.4 Game Theory Problems References Chapter 14: Probabilistic Inventory Models 14.1 Continuous Review Models 14.2 Single-Period Models 14.3 Multiperiod Model Problems References Chapter 15 Queueing Systems 15.1 Why Study Queues? 15.2 Elements of a Queuing Model 15.3 Role of Exponential Distribution 15.4 Pure Birth and Death Models (Relationship between the Exponential and Poisson Distributions) 15.5 Generalized Poisson Queuing Model 15.6 Specialized Poisson Queues 15.7 (M/G/1):(GD/Inf/Inf)-Pollaczek-Khintchine (P-K) Formula 15.8 Other Queuing Models 15.9 Queueing Decision Models Problems References Chapter 16: Simulation Modeling 16.1 Monte Carlo Simulation16.2 Types of Simulation16.3 Elements of Discrete-Event Simulation16.4 Generation of Random Numbers16.5 Mechanics of Discrete Simulation16.6 Methods for Gathering Statistical Observations16.7 Simulation Languages Problems References Chapter 17: Markov Chains17.1 Definition of a Markov Chain 17.2 Absolute and n-Step Transition Probabilities 17.3 Classification of the States in a Markov Chain 17.4Steady-State Probabilities and Mean Return Times of Ergodic Chains 17.5 First Passage Time 17.6 Analysis of Absorbing States Problems References Chapter 18: Classical Optimization Theory 18.1 Unconstrained Problems 18.2 Constrained Problems Problems References Chapter 19: Nonlinear Programming Algorithms 19.1 Unconstrained Algorithms 19.2 Constrained Algorithms Problems References Appendix A: AMPL Modeling LanguageA.1 Rudimentary AMPL ModelA.2 Components of AMPL ModelA.3 Mathematical Expressions and Computed ParametersA.4 Subsets and Indexed SetsA.5 Accessing External FilesA.6 Interactive CommandsA.7 Iterative and Conditional Execution of AMPL CommadsA.8 Sensitivity Analysis Using AMPL Reference Appendix B: Statistical Tables Appendix C: Partial Answers to Selected Problems Index On the CD Chapter 20: Additional Network and LP Algorithms20.1 Minimim-Cost Capacitated Flow Problem20.2 Decomposition Alogrithm20.3 Karmarkar Interior-Point Method Problems References Chapter 21: Forecasting Models21.1 Moving Average Technique21.2 Exponential Smoothing21.3 Maximization of the Event of Achieving a Goal Problems References Chapter 22: Probabilistic Dynamic Programming22.1 A Game of Chance22.2 Investment Problem22.3 Maximization of the Event of Achieving a Goal Problems References Chapter 23: Markovian Decision Process23.1 Scope of the Markovian Decision Problem23.2 Finite-Stage Dynamic Programming Model23.3 Infinite-Stage Model23.4 Linear Programming Solution Problems References Chapter 24: Case AnalysisCase 1: Airline Fuel Allocation Using Optimum TankeringCase 2: Optimization of Heart Valves ProductionCase 3: Scheduling Appointments at Australian Tourist Commission Trade EventsCase 4: Saving Federal Travel DollarsCase 5: Optimal Ship Routing and Personnel Assignments for Naval Recruitment in ThailandCase 6: Allocation of Operating Room Time in Mount Sinai HospitalCase 7: Optimizing Trailer Payloads at PFG Building GlassCase 8: Optimization of Crosscutting and Log Allocation at WeyerhaeuserCase 9: Layout Planning of a Computer Integrated Manufacturing (CIM) FacilityCase 10: Booking Limits in Hotel ReservationsCase 11: Casey's Problem: Interpreting and Evaluating a New TestCase 12: Ordering Golfers on the Final Day of Ryder Cup MatchesCase 13: Inventory Decisions in Dell's Supply ChainCase 14: Analysis of an Internal Transport System in a Manufacturing PlantCase 15: Telephone Sales Manpower Planning at Qantas Airways Appendix D: Review of Vectors and Matrices D.1 Vectors D.2 Matrices D.3 Quadratic Forms D.4 Convex and Concave Functions Problems References Appendix E: Case Studies