Enhanced descriptions from Syndetics:

This book makes a strong case for taking advantage of the best of two disciplines--health care and operational systems engineering (a combination of science and mathematics to describe, analyze, plan, design, and integrate systems with complex interactions among people, processes, materials, equipment, and facilities)-to improve the efficiency and quality of health care delivery, as well as health care outcomes. Those most interested in pursuing this approach include leaders in the U.S. Department of Defense (DOD) and Department of Veterans Affairs, who are committed to finding ways of improving the quality of care for military personnel, veterans, and their families. Intrigued by the possibilities, DOD decided to sponsor a series of workshops to explore the potential of operational systems engineering principals and tools for military health care, beginning with the diagnosis and care of traumatic brain injury (TBI), one of the most prevalent, difficult and challenging injuries suffered by warriors in Iraq and Afghanistan.

Table of contents provided by Syndetics

• Chapter 1 Decision Analysis (p. 1)
• 1.1 A Decision Tree Model and its Analysis (p. 2)
• 1.2 Summary of the General Method of Decision Analysis (p. 16)
• 1.3 Another Decision Tree Model and its Analysis (p. 17)
• 1.4 The Need for a Systematic Theory of Probability (p. 30)
• 1.5 Further Issues and Concluding Remarks on Decision Analysis (p. 33)
• 1.6 Case Modules (p. 35)
• Kendall Crab and Lobster, Inc. (p. 35)
• Buying a House (p. 38)
• The Acquisition of DSOFT (p. 38)
• National Realty Investment Corporation (p. 39)
• 1.7 Exercises (p. 44)
• Chapter 2 Fundamentals of Discrete Probability (p. 49)
• 2.1 Outcomes, Probabilities and Events (p. 50)
• 2.2 The Laws of Probability (p. 51)
• 2.3 Working with Probabilities and Probability Tables (p. 54)
• 2.4 Random Variables (p. 65)
• 2.5 Discrete Probability Distributions (p. 66)
• 2.6 The Binomial Distribution (p. 67)
• 2.7 Summary Measures of Probability Distributions (p. 72)
• 2.8 Linear Functions of a Random Variable (p. 79)
• 2.9 Covariance and Correlation (p. 82)
• 2.10 Joint Probability Distributions and Independence (p. 86)
• 2.11 Sums of Two Random Variables (p. 88)
• 2.12 Some Advanced Methods in Probability* (p. 91)
• 2.13 Summary (p. 96)
• 2.14 Case Modules (p. 97)
• Arizona Instrumentation, Inc. and the Economic Development Board of Singapore (p. 97)
• San Carlos Mud Slides (p. 98)
• Graphic Corporation (p. 99)
• 2.15 Exercises (p. 100)
• Chapter 3 Continuous Probability Distributions and Their Applications (p. 111)
• 3.1 Continuous Random Variables (p. 111)
• 3.2 The Probability Density Function (p. 112)
• 3.3 The Cumulative Distribution Function (p. 115)
• 3.4 The Normal Distribution (p. 120)
• 3.5 Computing Probabilities for the Normal Distribution (p. 127)
• 3.6 Sums of Normally Distributed Random Variables (p. 132)
• 3.7 The Central Limit Theorem (p. 135)
• 3.8 Summary (p. 139)
• 3.9 Exercises (p. 139)
• Chapter 4 Statistical Sampling (p. 147)
• 4.1 Random Samples (p. 148)
• 4.2 Statistics of a Random Sample (p. 150)
• 4.3 Confidence Intervals for the Mean, for Large Sample Size (p. 161)
• 4.4 The t-Distribution (p. 165)
• 4.5 Confidence Intervals for the Mean, for Small Sample Size (p. 166)
• 4.6 Estimation and Confidence Intervals for the Population Proportion (p. 169)
• 4.7 Experimental Design (p. 174)
• 4.8 Comparing Estimates of the Mean of Two Distributions (p. 178)
• 4.9 Comparing Estimates of the Population Proportion of Two Populations (p. 180)
• 4.10 Summary and Extensions (p. 182)
• 4.11 Case Modules (p. 183)
• Consumer Convenience, Inc. (p. 183)
• Posidon, Inc. (p. 184)
• Housing Prices in Lexington, Massachusetts (p. 185)
• Scallop Sampling (p. 185)
• 4.12 Exercises (p. 189)
• Chapter 5 Simulation Modeling: Concepts and Practice (p. 195)
• 5.1 A Simple Problem: Operations at Conley Fisheries (p. 196)
• 5.2 Preliminary Analysis of Conley Fisheries (p. 197)
• 5.3 A Simulation Model of the Conley Fisheries Problem (p. 199)
• 5.4 Random Number Generators (p. 201)
• 5.5 Creating Numbers that Obey a Discrete Probability Distribution (p. 203)
• 5.6 Creating Numbers that Obey a Continuous Probability Distribution (p. 205)
• 5.7 Completing the Simulation Model of Conley Fisheries (p. 211)
• 5.8 Using the Sample Data for Analysis (p. 213)
• 5.9 Summary of Simulation Modeling, and Guidelines on the Use of Simulation (p. 217)
• 5.10 Computer Software for Simulation Modeling (p. 217)
• 5.11 Typical Uses of Simulation Models (p. 218)
• 5.12 Case Modules (p. 219)
• The Gentle Lentil Restaurant (p. 219)
• To Hedge or not to Hedge? (p. 223)
• Ontario Gateway (p. 228)
• Casterbridge Bank (p. 235)
• Chapter 6 Regression Models: Concepts and Practice (p. 245)
• 6.1 Prediction Based on Simple Linear Regression (p. 246)
• 6.2 Prediction Based on Multiple Linear Regression (p. 253)
• 6.3 Using Spreadsheet Software for Linear Regression (p. 258)
• 6.4 Interpretation of Computer Output of a Linear Regression Model (p. 259)
• 6.5 Sample Correlation and R[superscript 2] in Simple Linear Regression (p. 271)
• 6.6 Validating the Regression Model (p. 274)
• 6.7 Warnings and Issues in Linear Regression Modeling (p. 279)
• 6.8 Regression Modeling Techniques (p. 283)
• 6.9 Illustration of the Regression Modeling Process (p. 288)
• 6.10 Summary and Conclusions (p. 294)
• 6.11 Case Modules (p. 295)
• Predicting Heating Oil Consumption at OILPLUS (p. 295)
• Executive Compensation (p. 297)
• The Construction Department at Croq'Pain (p. 299)
• Sloan Investors, Part I (p. 306)
• 6.12 Exercises (p. 313)
• Chapter 7 Linear Optimization (p. 323)
• 7.1 Formulating a Management Problem as a Linear Optimization Model (p. 324)
• 7.2 Key Concepts and Definitions (p. 332)
• 7.3 Solution of a Linear Optimization Model (p. 335)
• 7.4 Creating and Solving a Linear Optimization Model in a Spreadsheet (p. 347)
• 7.5 Sensitivity Analysis and Shadow Prices on Constraints (p. 354)
• 7.6 Guidelines for Constructing and Using Linear Optimization Models (p. 365)
• 7.7 Linear Optimization Under Uncertainty* (p. 367)
• 7.8 A Brief Historical Sketch of the Development of Linear Optimization (p. 374)
• 7.9 Case Modules (p. 375)
• Short-Run Manufacturing Problems at DEC (p. 375)
• Sytech International (p. 380)
• Filatoi Riuniti (p. 389)
• 7.10 Exercises (p. 397)
• Chapter 8 Nonlinear Optimization (p. 411)
• 8.1 Formulating a Management Problem as a Nonlinear Optimization Model (p. 412)
• 8.2 Graphical Analysis of Nonlinear Optimization Models in Two Variables (p. 420)
• 8.3 Computer Solution of Nonlinear Optimization Problems (p. 425)
• 8.4 Shadow Prices Information in Nonlinear Optimization Models (p. 428)
• 8.5 A Closer Look at Portfolio Optimization (p. 431)
• 8.6 Taxonomy of the Solvability of Nonlinear Optimization Problems* (p. 432)
• 8.7 Case Modules (p. 436)
• Endurance Investors (p. 436)
• Capacity Investment, Marketing, and Production at ILG, Inc. (p. 442)
• 8.8 Exercises (p. 444)
• Chapter 9 Discrete Optimization (p. 451)
• 9.1 Formulating a Management Problem as a Discrete Optimization Model (p. 452)
• 9.2 Graphical Analysis of Discrete Optimization Models in Two Variables (p. 461)
• 9.3 Computer Solution of Discrete Optimization Problems (p. 464)
• 9.4 The Branch-and-Bound Method for Solving a Discrete Optimization Model* (p. 468)
• 9.5 Summary (p. 471)
• 9.6 Case Modules (p. 471)
• International Industries, Inc. (p. 471)
• Supply Chain Management at Dellmar, Inc. (p. 474)
• The National Basketball Dream Team (p. 476)
• 9.7 Exercises (p. 478)
• Chapter 10 Intergration in the Art of Decision Modeling (p. 485)
• 10.1 Management Science Models in the Airline Industry (p. 486)
• 10.2 Management Science Models in the Investment Management Industry (p. 496)
• 10.3 A Year in the Life of a Manufacturing Company (p. 498)
• 10.4 Summary (p. 501)
• 10.5 Case Modules (p. 502)
• Sloan Investors, Part II (p. 502)
• Revenue Management at Atlantic Air (p. 503)
• A Strategic Alliance for the Lexington Laser Corporation (p. 508)
• Yield of a Multi-step Manufacturing Process (p. 510)
• Prediction of Yields in Manufacturing (p. 512)
• Allocation of Production Personnel (p. 513)
• Appendix (p. 517)
• References (p. 521)
• Index (p. 525)

Author notes provided by Syndetics