数据、模型与决策：管理科学基础 英文版PDF|Epub|txt|kindle电子书版本网盘下载

数据、模型与决策：管理科学基础 英文版PDF格式电子书版下载

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CHAPTER 1 DECISION ANALYSIS1

CHAPTER 1 DECISION ANALYSIS1

1.1 A Decision Tree Model and its Analysis2

1.2 Summary of the General Method of Decision Analysis16

1.3 Another Decision Tree Model and its Analysis17

1.4 The Need for a Systematic Theory of Probability30

1.5 Further Issues and Concluding Remarks on Decision Analysis33

Kendall Crab and Lobster, Inc.35

1.6 Case Modules35

The Acquisition of DSOFT38

Buying a House38

National Realty Investment Corporation39

1.7 Exercises44

CHAPTER 2 FUNDAMENTALS OF DISCRETE PROBABILITY49

CHAPTER 2 FUNDAMENTALS OF DISCRETE PROBABILITY49

2.1 Outcomes, Probabilities and Events50

2.2 The Laws of Probability51

2.3 Working with Probabilities and Probability Tables54

2.4 Random Variables65

2.5 Discrete Probability Distributions66

2.6 The Binomial Distribution67

2.7 Summary Measures of Probability Distributions72

2.8 Linear Functions of a Random Variable79

2.9 Covariance and Correlation82

2.10 Joint Probability Distributions and Independence86

2.11 Sums of Two Random Variables88

2.12 Some Advanced Methods in Probability*91

2.13 Summary96

Arizona Instrumentation, Inc and the Economic Development Board of Singapore97

2.14 Case Modules97

San Carlos Mud Slides98

Graphic Corporation99

2.15 Exercises100

CHAPTER 3 CONTINUOUS PROBABILITY DISTRIBUTIONS AND THEIR APPLICATIONS111

3.1 Continuous Random Variables111

CHAPTER 3 CONTINUOUS PROBABILITY DISTRIBUTIONS AND THEIR APPLICATIONS111

3.2 The Probability Density Function112

3.3 The Cumulative Distribution Function115

3.4 The Normal Distribution120

3.5 Computing Probabilities for the Normal Distribution127

3.6 Sums of Normally Distributed Random Variables132

3.7 The Central Limit Theorem135

3.8 Summary139

3.9 Exercises139

CHAPTER 4 STATISTICAL SAMPLING147

CHAPTER 4 STATISTICAL SAMPLING147

4.1 Random Samples148

4.2 Statistics of a Random Sample150

4.3 Confidence Intervals for the Mean, for Large Sample Size161

4.4 The t-Distribution165

4.5 Confidence Intervals for the Mean, for Small Sample Size166

4.6 Estimation and Confidence Intervals for the Population Proportion169

4.7 Experimental Design174

4.8 Comparing Estimates of the Mean of Two Distributions178

4.9 Comparing Estimates of the Population Proportion of Two Populations180

4.10 Summary and Extensions182

4.11 Case Modules183

Consumer Convenience, Inc.183

POSIDON, Inc.184

Housing Prices in Lexington, Massachusetts185

Scallop Sampling185

4.12 Exercises189

CHAPTER 5 SIMULATION MODELING： CONCEPTS AND PRACTICE195

CHAPTER 5 SIMULATION MODELING: CONCEPTS AND PRACTICE195

5.1 A Simple Problem: Operations at Conley Fisheries196

5.2 Preliminary Analysis of Conley Fisheries197

5.3 A Simulation Model of the Conley Fisheries Problem199

5.4 Random Number Generators201

5.5 Creating Numbers that Obey a Discrete Probability Distribution203

5.6 Creating Numbers that Obey a Continuous Probability Distribution205

5.7 Completing the Simulation Model of Conley Fisheries211

5.8 Using the Sample Data for Analysis213

5.10 Computer Software for Simulation Modeling217

5.9 Summary of Simulation Modeling and Guidelines on the Use of Simulation217

5.11 Typical Uses of Simulation Models218

The Gentle Lentil Restaurant219

5.12 Case Modules219

To Hedge or not to Hedge?223

Ontario Cateway228

Casterbridge Bank235

CHAPTER 6 REGRESSION MODELS: CONCEPTS AND PRACTICE245

CHAPTER 6 REGRESSION MODELS: CONCEPTS AND PRACTICE245

6.1 Prediction Based on Simple Linear Regression246

6.2 Prediction Based on Multiple Linear Regression253

6.3 Using Spreadsheet Software for Linear Regression258

6.4 Interpretation of Computer Output of a Linear Regression Model259

6.5 Sample Correlation and R2 in Simple Linear Regression271

6.6 Validating the Regression Model274

6.7 Warnings and Issues in Linear Regression Modeling279

6.8 Regression Modeling Techniques283

6.9 Illustration of the Regression Modeling Process288

6.10 Summary and Conclusions294

6.11 Case Modules295

Predicting Heating Oil Consumption at OILPLUS295

Executive Compensation297

The Construction Department at Croq Pain299

Sloan Investors, Part I306

6.12 Exercises313

CHAPTER 7 LINEAR OPTIMIZATION323

CHAPTER 7 LINEAR OPTIMIZATION323

7.1 Formulating a Management Problem as a Linear Optimization Model324

7.2 Key Concepts and Definitions332

7.3 Solution of a Linear Optimization Model335

7.4 Creating and Solving a Linear Optimization Model in a Spreadsheet347

7.5 Sensitivity Analysis and Shadow Prices on Constraints354

7.6 Guidelines for Constructing and Using Linear Optimization Models365

7.7 Linear Optimization Under Uncertainty*367

7.8 A Brief Historical Sketch of the Development of Linear Optimization374

7.9 Case Modules375

Short-Run Manufacturing Problems at DEC375

Sytech International380

Filatoi Riuniti389

7.10 Exercises397

CHAPTER 8 NONLINEAR OPTIMIZATION411

CHAPTER 8 NONLINEAR OPTIMIZATION411

8.1 Formulating a Management Problems as a Nonlinear Optimization Model412

8.2 Graphical Analysis of Nonlinear Optimization Models in Two Variables420

8.3 Computer Solution of Nonlinear Optimization Problems425

8.4 Shadow Prices Information in Nonlinear Optimization Models428

8.5 A Closer Look at Portfolio Optimization431

8.6 Taxonomy of the Solvability of Nonlinear Optimization Problems*432

8.7 Case Modules436

Endurance Investors436

Capacity Investment, Marketing and Production at ILG, Inc.442

8.8 Exercises444

CHAPTER 9 DISCRETE OPTIMIZATION451

CHAPTER 9 DISCRETE OPTIMIZATION451

9.1 Formulating a Management Problem as a Discrete Optimization Model452

9.2 Graphical Analysis of Discrete Optimization Models in Two Variables461

9.3 Computer Solution of Discrete Optimization Problems464

9.4 The Branch-and-Bound Method for Solving a Discrete Optimization Model*468

9.5 Summary471

9.6 Case Modules471

International Industries, Inc.471

The National Basketball Dream Team476

9.7 Exercises478

CHAPTER 10 INTEGRATION IN THE ART OF DECISION MODELING485

CHAPTER 10 INTEGRATION IN THE ART OF DECISION MODELING485

10.1 Management Science Models in the Airline Industry486

10.2 Management Science Models in the Investment Management Industry496

10.3 A Year in the Lift of a Manufacturing Company498

10.4 Summary501

10.5 Case Modules502

Sloan Investors, PartⅡ502

Revenue Management at Atlantic Air503

A Strategic Alliance for the Lexington Laser Corporation508

Yield of a Multi-step Manufacturing Process510

Prediction of Yields in Manufacturing512

Allocation of Production Personnel513

APPENDIX517

APPENDIX517

REFERENCES521

REFERENCES521

INDEX525

INDEX525