Practical Management Science, 6th Edition PDF by Wayne L. Winston, S. Christian Albright

By

Practical Management Science, 6th Edition

By Wayne L. Winston, S. Christian Albright

Practical Management Science

Contents

Preface xiii

CHAPTER 1 Introduction to Modeling 1

1.1 Introduction 3

1.2 A Capital Budgeting Example 3

1.3 Modeling versus Models 6

1.4 A Seven-Step Modeling Process 7

1.5 A Great Source for Management Science Applications: Interfaces 13

1.6 Why Study Management Science? 13

1.7 Software Included with This Book 15

1.8 Conclusion 17

CHAPTER 2 Introduction to Spreadsheet Modeling 19

2.1 Introduction 20

2.2 Basic Spreadsheet Modeling: Concepts and Best Practices 21

2.3 Cost Projections 25

2.4 Breakeven Analysis 31

2.5 Ordering with Quantity Discounts and Demand Uncertainty 39

2.6 Estimating the Relationship between

Price and Demand 44

2.7 Decisions Involving the Time Value of Money 54

2.8 Conclusion 59

Appendix Tips for Editing and Documenting Spreadsheets 64

Case 2.1 Project Selection at Ewing Natural Gas 66

Case 2.2 New Product Introduction at eTech 68

CHAPTER 3 Introduction to Optimization Modeling 71

3.1 Introduction 72

3.2 Introduction to Optimization 73

3.3 A Two-Variable Product Mix Model 75

3.4 Sensitivity Analysis 87

3.5 Properties of Linear Models 97

3.6 Infeasibility and Unboundedness 100

3.7 A Larger Product Mix Model 103

3.8 A Multiperiod Production Model 111

3.9 A Comparison of Algebraic and Spreadsheet Models 120

3.10 A Decision Support System 121

3.11 Conclusion 123

Appendix Information on Optimization Software 130

Case 3.1 Shelby Shelving 132

Chapter 4 Linear Programming Models 135

4.1 Introduction 136

4.2 Advertising Models 137

4.3 Employee Scheduling Models 147

4.4 Aggregate Planning Models 155

4.5 Blending Models 166

4.6 Production Process Models 174

4.7 Financial Models 179

4.8 Data Envelopment Analysis (Dea) 191

4.9 Conclusion 198

Case 4.1 Blending Aviation Gasoline at Jansen Gas 214

CASE 4.2 Delinquent Accounts at GE Capital 216

CASE 4.3 Foreign Currency Trading 217

CHAPTER 5 Network Models 219

5.1 Introduction 220

5.2 Transportation Models 221

5.3 Assignment Models 233

5.4 Other Logistics Models 240

5.5 Shortest Path Models 249

5.6 Network Models in the Airline Industry 258

5.7 Conclusion 267

Case 5.1 Optimized Motor Carrier Selection at Westvaco 274

Chapter 6 Optimization Models with Integer Variables 277

6.1 Introduction 278

6.2 Overview of Optimization with Integer Variables 279

6.3 Capital Budgeting Models 283

6.4 Fixed-Cost Models 290

6.5 Set-Covering and Location-Assignment Models 303

6.6 Cutting Stock Models 320

6.7 Conclusion 324

Case 6.1 Giant Motor Company 334

Case 6.2 Selecting Telecommunication Carriers to

Obtain Volume Discounts 336

Case 6.3 Project Selection at Ewing Natural Gas 337

Chapter 7 Nonlinear Optimization Models 339

7.1 Introduction 340

7.2 Basic Ideas of Nonlinear Optimization 341

7.3 Pricing Models 347

7.4 Advertising Response and Selection Models 365

7.5 Facility Location Models 374

7.6 Models for Rating Sports Teams 378

7.7 Portfolio Optimization Models 384

7.8 Estimating the Beta of a Stock 394

7.9 Conclusion 398

Case 7.1 Gms Stock Hedging 405

Chapter 8 Evolutionary Solver: An Alternative

Optimization Procedure 407

8.1 Introduction 408

8.2 Introduction to Genetic Algorithms 411

8.3 Introduction to Evolutionary Solver 412

8.4 Nonlinear Pricing Models 417

8.5 Combinatorial Models 424

8.6 Fitting an S-Shaped Curve 435

8.7 Portfolio Optimization 439

8.8 Optimal Permutation Models 442

8.9 Conclusion 449

Case 8.1 Assigning Mba Students to Teams 454

Case 8.2 Project Selection at Ewing Natural Gas 455

Chapter 9 Decision Making under Uncertainty 457

9.1 Introduction 458

9.2 Elements of Decision Analysis 460

9.3 Single-Stage Decision Problems 467

9.4 The PrecisionTree Add-In 471

9.5 Multistage Decision Problems 474

9.6 The Role of Risk Aversion 492

9.7 Conclusion 499

CASE 9.1 Jogger Shoe Company 510

CASE 9.2 Westhouser Paper Company 511

CASE 9.3 Electronic Timing System for Olympics 512

CASE 9.4 Developing a Helicopter Component for the Army 513

Chapter 10 Introduction to Simulation Modeling 515

10.1 Introduction 516

10.2 Probability Distributions for Input Variables 518

10.3 Simulation and the Flaw of Averages 537

10.4 Simulation with Built-in Excel Tools 540

10.5 Introduction to @RISK 551

10.6 The Effects of Input Distributions on Results 568

10.7 Conclusion 577

Appendix Learning More About @Risk 583

CASE 10.1 Ski Iacket Production 584

CASE 10.2 Ebony Bath Soap 585

CASE 10.3 Advertising Effectiveness 586

CASE 10.4 New Project Introduction at eTech 588

Chapter 11 Simulation Models 589

11.1 Introduction 591

11.2 Operations Models 591

11.3 Financial Models 607

11.4 Marketing Models 631

11.5 Simulating Games of Chance 646

11.6 Conclusion 652

Appendix Other Palisade Tools for Simulation 662

CASE 11.1 College Fund Investment 664

CASE 11.2 Bond Investment Strategy 665

CASE 11.3 Project Selection Ewing Natural Gas 666

Chapter 12 Queueing Models 667

12.1 Introduction 668

12.2 Elements of Queueing Models 670

12.3 The Exponential Distribution 673

12.4 Important Queueing Relationships 678

12.5 Analytic Steady-State Queueing Models 680

12.6 Queueing Simulation Models 699

12.7 Conclusion 709

Case 12.1 Catalog Company Phone Orders 713

Chapter 13 Regression and Forecasting Models 715

13.1 Introduction 716

13.2 Overview of Regression Models 717

13.3 Simple Regression Models 721

13.4 Multiple Regression Models 734

13.5 Overview of Time Series Models 745

13.6 Moving Averages Models 746

13.7 Exponential Smoothing Models 751

13.8 Conclusion 762

Case 13.1 Demand for French Bread at Howie’s Bakery 768

Case 13.2 Forecasting Overhead at Wagner Printers 769

Case 13.3 Arrivals at the Credit Union 770

Chapter 14 Data Mining 771

14.1 Introduction 772

14.2 Classification Methods 774

14.3 Clustering Methods 795

14.4 Conclusion 806

Case 14.1 Houston Area Survey 808

References 809

Index 815

MindTap Chapters

Chapter 15 Project Management 15-1

15.1 Introduction 15-2

15.2 The Basic CPM Model 15-4

15.3 Modeling Allocation of Resources 15-14

15.4 Models with Uncertain Activity Times 15-30

15.5 A Brief Look at Microsoft Project 15-35

15.6 Conclusion 15-39

Chapter 16 Multiobjective Decision Making 16-1

16.1 Introduction 16-2

16.2 Goal Programming 16-3

16.3 Pareto Optimality and Trade-Off Curves 16-12

16.4 The Analytic Hierarchy Process (AHP) 16-20

16.5 Conclusion 16-25

Chapter 17 Inventory and Supply Chain Models 17-1

17.1 Introduction 17-2

17.2 Categories of Inventory and Supply Chain Models 17-3

17.3 Types of Costs in Inventory and Supply Chain Models 17-5

17.4 Economic Order Quantity (EOQ) Models 17-6

17.5 Probabilistic Inventory Models 17-21

17.6 Ordering Simulation Models 17-34

17.7 Supply Chain Models 17-40

17.8 Conclusion 17-50

Case 17.1 Subway Token Hoarding 17-57

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