Chapter 1 Proactive Decision Making 1
Routine Decisions 2
The Challenges of Proactive Decision Making 3
Alternatives 3
Assumptions—Structure 4
Assumptions—Assessments 5
Performance 6
Summary 7
Chapter 2 Alternatives 9
Small Number of Alternatives 9
Sequential Decisions 11
A Single Decision Quantity 12
Two or More Decision Quantities 17
Decision Rules 17
Summary 18
Chapter 3 Structuring Assumptions in Decision Making 19
Structuring Relationships Using an Influence Diagram 20
Structuring a Sequence of Decisions and Uncertainties Using a Decision Tree 26
Influence Diagrams with Uncertain Quantities 31
Final Examples of How to Develop an Influence Diagram 34
The Use of Influence Diagrams and Decision Trees 37
Case：Destiny Consulting Group 39
Chapter 4 Assessment 42
Sensitivity Analysis 43
The Language of Probability 48
Uncertainties with a Few Potential Outcomes 48
Uncertainties with Many Potential Outcomes 51
Summary Measures of Probability Distributions 52
Deriving the Probability Distribution for Performance 55
Summary 56
Relevant Monetary Flows 59
Chapter 5 Performance 59
Evaluating Alternatives under Uncertainty 62
Few Potential Outcomes 62
Many Potential Outcomes 67
Summary 74
Chapter 6 Risk Management 76
Value of Information 76
Perfect Information 77
Imperfect Information 79
Value of Control 81
Perfect Control 82
Control of Continuously Ranging Quantities 82
Adding Value and Reducing Risk 83
Summary 86
Chapter 7 Evaluating Multiperiod Performance 87
Cash Flow 88
An Example 89
Time Value of Money 91
Accumulated Value 92
Present Value and Net Present Value 94
Formulas for Accumulated and Present Value Calculations 97
Streams in Perpetuity 97
Pretax versus Aftertax Analyses 98
The Reinvestment Rate 98
Hurdle Rate 99
Internal Rate of Return 99
Nominal versus Effective Rates of Return 101
Chapter 8 Multiobjective and Multistakeholder Choice 103
The Generic Choice Problem 103
Example 104
First-Round Eliminations 105
Dominance 105
Decision Rules without Tradeoff Judgments 107
Satisficing 108
The Lexicographic Rule 108
Rate and Weight：Linear Additive Scoring Rules 109
Rating Alternatives 109
Weighting Attributes 110
Assumptions of Rate and Weight 115
Multiple Stakeholder Problems 116
Appendix 1 Comments on the Dependence of Weights on the Scaling of Attributes 116
Exercises 119
Chapter 9 Risk Preference and Utility 120
The Utility of Monetary Consequences 120
Risk Aversion 123
Constant Risk Aversion：Negative Exponential Utility 124
Decreasing Risk Aversion：Logarithmic Utility 126
Using a Utility Curve for Risk Analysis 129
Separation of Risk-Return and Mean-Variance Analysis 131
Corporate Risk Policy 132
Exercises 133
Chapter 10 Competitor Analysis 134
Characterizing Competitive Situations 135
Matrix Format 137
Classical Structures 141
No(or Little) Conflict 141
Prisoner s Dilemma 142
Preemption 144
Summary 145
Chapter 11 Probability Distributions 147
The Language of Probability Distributions 147
The Probability Mass Function 148
The Cumulative Distribution Function 149
Continuous and Many-Valued Uncertain Quantities 152
Assessment：Capturing Personal Judgment 156
An Example of Assessing a Probability Distribution 159
Assessment：Using Historical Data as a Guide 160
Identifying Suitable Data 161
Using the Suitable Data as a Guide 162
Adjusting Data for One Distinguishing Factor 167
Assessment：Appealing to Underlying Structure 168
The Binomial Distribution 169
The Normal Distribution 172
The Poisson Distribution 177
The Exponential Distribution 178
Subjective Biases and Assessment 180
Summary 182
Chapter 12 Sampling 183
Forecasting Sample Results 184
Forecasting a Sample Average 186
Forecasting a Sample Proportion 188
Using Sample Results to Draw Inferences about the Underlying Probability Distribution 191
Inferences about the Mean of the Underlying Probability Distribution 192
Inferences about the Underlying Probability 194
Using Sample Results to Forecast Future Sample Results 195
Using Sample Results to Forecast a Future Sample Average 196
Using Sample Results to Forecast a Future Sample Proportion 197
Summary 198
Chapter 13 Time-Series Forecasting 199
Basic Approaches for One-Period Forecasts 200
Simple Approaches 200
Moving Average 201
Smoothed Average 202
Comparison of Forecasts 203
Precision 204
Bias 205
Exploiting Multiperiod Patterns 207
Treating Seasonality 208
Deseasonalizing a Time Series 208
Forecasting the Deseasonalized Series 211
Decomposition of Time Series into Seasonality and Trend Components 213
Reseasonalizing the Forecast 213
Generating the Probability Distribution Forecast 213
Separating out Seasonality 214
Extrapolating Trend and Cycle Components 215
Holt s Model：Exponential Smoothing with Trend 217
Winter s Model：Exponential Smoothing with Trend and Seasonality 220
Other Advanced Techniques 221
Considerations in Preparing and Using a Forecast 222
Chapter 14 Regression：Forecasting Using Explanatory Factors 224
The Simple Linear Model 224
Fitting the Model Using “Least Squares” 227
Important Properties of the Least-Squares Regression Line 229
Summary Regression Statistics 230
Standard Error of Estimate 232
Adjusted R Square 233
Standard Error of the Coefficients 235
Assumptions behind the Linear Regression Model 236
Linearity 237
Independence 239
Homoscedasticity 241
Normality 242
Summary of Regression Assumptions 243
Model-Building Philosophy 244
Uses of the Linear Model 245
Nature of the Relationship among Variables 246
The Importance of the Underlying Relationship to the Use of the Model 247
Model-Building Procedure 249
Common Mistakes 253
Summary 254
Forecasting Using the Linear Regression Model 255
Point Forecast 255
Interval Forecast 255
Analogy to Simple Random Sampling 257
Using Dummy Variables to Represent Categorical Variables 259
Example 259
Dummy Variables for More than Two Groups 261
Useful Data Transformations 262
Example 263
Choosing a Transformation 267
Transforming the Y-Variable 270
Chapter 15 Discrete-Event Simulation 273
An Example Application of Discrete-Event Simulation 274
The Model 275
Important Issues in Discrete-Event Simulation 283
Calibrating the Uncertainties 283
Validating the Model 284
Avoiding Peculiarities Associated with Start-up 285
Terminating the Model Run 285
Summary 286
Chapter 16 Introduction to Optimization Models 287
Transforming an Evaluation Model into an Optimization Model 288
Example 1：Optimal Order Quantity 288
Example 2：Product Mix Planning 299
Example 3：Facility Location 301
Summary of Examples 307
Categorizing and Solving Optimization Models 308
Example 1：Nonlinear Programming 308
Example 2：Linear Programming 312
Example 3：Integer Programming 314
Uncertainty in Optimization Models：Sensitivity Analysis 319
Lagrange Multipliers 319
Linear Programming Models 322
Building an Optimization Model from Scratch 326
Chapter 17 The Mathematics of Optimization 332
Functions 333
Algebraic Framework for Optimization Models 333
General Structure of an Optimization Model 335
Integer Programming 337
Linear Programming (LP) 337
Graphical Representation of Example 2 338
The Simplex Algorithm 341
Some Final Comments on the Simplex Algorithm and LP 344
Karmarkar s Algorithm：An Alternative Approach to Solving LP Models 345
Nonlinear Programming (NLP) 346
Levers to Control the GS Solution Approach 349
Integer Programming (IP) 352
Final Observations：LP，NLP，and IP 358
Summary 360
Cases 361
Case 1：American Lawbook Corporation（A） 361
Case 2：American Lawbook Corporation（B） 372
Case 3：Amore Frozen Foods 375
Case 4：Athens Glass Works 381
Case 5：Buckeye Power Light Company 384
Case 6：Buckeye Power Light Company Supplement 389
Case 7：California Oil Company 397
Case 8：C．K．Coolidge，Inc．（A） 401
Case 9：The Commerce Tavern 413
Case 10：CyberLab：A New Business Opportunity for PRICO（A） 420
Case 11：CyberLab：Supplement 428
Case 12：CyberLab：A New Business Opportunity for PRICO（B） 430
Case 13：Dhahran Roads（A） 432
Case 14：Dhahran Roads（B） 434
Case 15：Discounted Cash Flow Exercises 436
Case 16：Edgcomb Metals（A） 438
Case 17：Florida Glass Company（A） 447
Case 18：Florida Glass Company（A）Supplement 454
Case 19：Foulke Consumer Products，Inc． 457
Case 20：Foulke Consumer Products，Inc．，Supplement 463
Case 21：Freemark Abbey Winery 475
Case 22：Galaxy Micro Systems 478
Case 23：Galaxy Micro Systems Supplement 480
Case 24：George s T-Shirts 481
Case 25：Harimann International 483
Case 26：Hightower Department Stores：Imported Stuffed Animals 490
Case 27：International Guidance and Controls 499
Case 28：Jade Shampoo（A） 501
Case 29：Jade Shampoo（B） 506
Case 30：Jaikumar Textiles，Ltd．;The Nylon Division（A） 509
Case 31：Jaikumar Textiles，Ltd．;The Nylon Division（B） 513
Case 32：Lesser Antilles Lines：The Island of San Huberto 515
Case 33：Lightweight Aluminum Company：The Lebanon Plant 524
Case 34：Lorex Pharmaceuticals 536
Case 35：Maxco，Inc．，and the Gambit Company 539
Case 36：The Oakland A s（A） 546
Case 37：The Oakland A s（A）Supplement 555
Case 38：The Oakland A s（B） 563
Case 39：Piedmont Airlines：Discount Seat Allocation（A） 566
Case 40：Piedmont Airlines：Discount Seat Allocation（B） 574
Case 41：Probability Assessment Exercise 579
Case 42：Problems in Regression 581
Case 43：Roadway Construction Company 585
Case 44：Shumway，Horch，and Sager（A） 588
Case 45：Shumway，Horch，and Sager（B） 591
Case 46：Sleepmore Mattress Manufacturing：Plant Consolidation 595
Case 47：Sprigg Lane（A） 600
Case 48：T．Rowe Price Associates 611
Case 49：Wachovia Bank and Trust Company，N．A．（B） 619
Case 50：Wachovia Bank and Trust Company，N．A．（B）：Supplement 622
Case 51：Waite First Securities 625
Case 52：The Waldorf Property 632