Quantitative analysis for management

Cover......Page 1
Copyright......Page 3
About the Authors......Page 4
Brief Contents......Page 6
Contents......Page 7
Preface......Page 14
Acknowledgments......Page 18
1. Introduction toQuantitative Analysis......Page 20
 1.2 What Is Quantitative Analysis?......Page 21
 1.3 Business Analytics......Page 22
  Developing a Model......Page 23
  Developing a Solution......Page 24
  Implementing the Results......Page 25
 1.5 How to Develop a Quantitative Analysis Model......Page 27
  Mathematical Models Categorized by Risk......Page 28
 1.6 The Role of Computers and Spreadsheet Models in the Quantitative Analysis Approach......Page 29
  Defining the Problem......Page 32
  Developing a Model......Page 33
  Developing a Solution......Page 34
  Analyzing the Results......Page 35
 Summary......Page 36
 Self-Test......Page 37
 Discussion Questions and Problems......Page 38
 Bibliography......Page 40
2. Probability Concepts and Applications......Page 42
  Two Basic Rules of Probability......Page 43
  Types of Probability......Page 44
  Mutually Exclusive and Collectively Exhaustive Events......Page 45
  Unions and Intersections of Events......Page 46
  Probability Rules for Unions, Intersections, and Conditional Probabilities......Page 47
 2.3 Revising Probabilities with Bayes’ Theorem......Page 48
 2.4 Further Probability Revisions......Page 50
 2.5 Random Variables......Page 51
  Expected Value of a Discrete Probability Distribution......Page 53
  Variance of a Discrete Probability Distribution......Page 54
  Probability Distribution of a Continuous Random Variable......Page 55
 2.7 The Binomial Distribution......Page 56
  Solving Problems with the Binomial Formula......Page 57
  Solving Problems with Binomial Tables......Page 58
 2.8 The Normal Distribution......Page 59
  Using the Standard Normal Table......Page 61
  Haynes Construction Company Example......Page 62
 2.9 The F Distribution......Page 65
 2.10 The Exponential Distribution......Page 67
  Arnold’s Muffler Example......Page 68
 2.11 The Poisson Distribution......Page 69
 Glossary......Page 71
 Key Equations......Page 72
 Solved Problems......Page 73
 Self-Test......Page 75
 Discussion Questions and Problems......Page 76
 Case Study: Indian Metro League......Page 82
 Bibliography......Page 83
3. Decision Analysis......Page 86
 3.2 The Six Steps in Decision Making......Page 87
 3.3 Types of Decision-Making Environments......Page 88
  Optimistic......Page 89
  Criterion of Realism (Hurwicz Criterion)......Page 90
  Minimax Regret......Page 91
  Expected Monetary Value......Page 92
  Expected Value of Perfect Information......Page 93
  Sensitivity Analysis......Page 95
 3.6 A Minimization Example......Page 96
  QM for Windows......Page 98
  Excel QM......Page 99
 3.8 Decision Trees......Page 100
  Sensitivity Analysis......Page 105
  Calculating Revised Probabilities......Page 106
  Potential Problem in Using Survey Results......Page 108
 3.10 Utility Theory......Page 109
  Measuring Utility and Constructing a Utility Curve......Page 110
  Utility as a Decision-Making Criterion......Page 113
 Glossary......Page 115
 Solved Problems......Page 116
 Self-Test......Page 121
 Discussion Questions and Problems......Page 122
 Case Study: Starting Right Corporation......Page 130
 Case Study: Blake Electronics......Page 131
 Bibliography......Page 133
4. Regression Models......Page 134
 4.2 Scatter Diagrams......Page 135
 4.3 Simple Linear Regression......Page 136
 4.4 Measuring the Fit of the Regression Model......Page 138
  Correlation Coefficient......Page 139
 4.5 Assumptions of the Regression Model......Page 141
 4.6 Testing the Model for Significance......Page 142
  The Analysis of Variance (ANOVA) Table......Page 144
  Excel 2013......Page 145
  Excel QM......Page 146
  QM for Windows......Page 148
 4.8 Multiple Regression Analysis......Page 149
  Evaluating the Multiple Regression Model......Page 150
  Jenny Wilson Realty Example......Page 151
 4.9 Binary or Dummy Variables......Page 152
 4.10 Model Building......Page 153
 4.11 Nonlinear Regression......Page 154
 4.12 Cautions and Pitfalls in Regression Analysis......Page 157
 Glossary......Page 158
 Key Equations......Page 159
 Solved Problems......Page 160
 Discussion Questions and Problems......Page 162
 Case Study: North–South Airline......Page 167
 Case Study: The Southern Motorcycle Company......Page 168
 Appendix 4.1: Formulas for Regression Calculations......Page 169
5. Forecasting......Page 172
  Qualitative Models......Page 173
 5.3 Components of a Time-Series......Page 174
 5.4 Measures of Forecast Accuracy......Page 176
  Weighted Moving Averages......Page 179
  Exponential Smoothing......Page 181
  Using Software for Forecasting Time Series......Page 183
  Exponential Smoothing with Trend......Page 186
  Trend Projections......Page 188
 5.7 Adjusting for Seasonal Variations......Page 190
  Calculating Seasonal Indices with No Trend......Page 191
  Calculating Seasonal Indices with Trend......Page 192
  The Decomposition Method......Page 193
  Software for Decomposition......Page 196
  Using Regression with Trend and Seasonal Components......Page 197
 5.9 Monitoring and Controlling Forecasts......Page 198
 Summary......Page 200
 Glossary......Page 201
 Solved Problems......Page 202
 Self-Test......Page 203
 Discussion Questions and Problems......Page 204
 Case Study: Forecasting Attendance at SWU Football Games......Page 207
 Case Study: Forecasting Monthly Sales......Page 208
 Case Study: Forecasting Commercial Vehicle Sales at ABCO......Page 209
 Bibliography......Page 215
6. Inventory Control Models......Page 216
 6.1 Introduction......Page 217
  Avoiding Stockouts and Shortages......Page 218
 6.3 Inventory Decisions......Page 219
 6.4 Economic Order Quantity: Determining How Much to Order......Page 220
  Inventory Costs in the EOQ Situation......Page 221
  Sumco Pump Company Example......Page 223
  Purchase Cost of Inventory Items......Page 224
  Sensitivity Analysis with the EOQ Model......Page 225
 6.5 Reorder Point: Determining When to Order......Page 226
 6.6 EOQ Without the Instantaneous Receipt Assumption......Page 227
  Annual Setup Cost or Annual Ordering Cost......Page 228
  Brown Manufacturing Example......Page 229
 6.7 Quantity Discount Models......Page 231
  Brass Department Store Example......Page 233
 6.8 Use of Safety Stock......Page 235
 6.9 Single-Period Inventory Models......Page 240
  Marginal Analysis with Discrete Distributions......Page 241
  Café du Donut Example......Page 242
  Newspaper Example......Page 243
 6.11 Dependent Demand: The Case for Material Requirements Planning......Page 245
  Material Structure Tree......Page 246
  Gross and Net Material Requirements Plan......Page 247
  Two or More End Products......Page 248
 6.12 Just-In-Time Inventory Control......Page 250
 6.13 Enterprise Resource Planning......Page 251
 Glossary......Page 252
 Key Equations......Page 253
 Solved Problems......Page 254
 Self-Test......Page 256
 Discussion Questions and Problems......Page 257
 Case Study: Martin-Pullin Bicycle Corporation......Page 264
 Case Study: Multiperiod Inventory Planning at ABYCO......Page 265
 Bibliography......Page 266
 Appendix 6.1: Inventory Control with QM for Windows......Page 267
7. Linear Programming Models: Graphical and Computer Methods......Page 270
 7.2 Requirements of a Linear Programming Problem......Page 271
  Flair Furniture Company......Page 272
  Graphical Representation of Constraints......Page 274
  Isoprofit Line Solution Method......Page 278
  Corner Point Solution Method......Page 281
  Slack and Surplus......Page 283
  Using QM for Windows......Page 284
  Using Excel’s Solver Command to Solve LP Problems......Page 285
  Using Excel QM......Page 288
  Holiday Meal Turkey Ranch......Page 290
  Unboundedness......Page 294
  Redundancy......Page 295
  Alternate Optimal Solutions......Page 296
 7.8 Sensitivity Analysis......Page 297
  High Note Sound Company......Page 298
  QM for Windows and Changes in Objective Function Coefficients......Page 299
  Excel Solver and Changes in Objective Function Coefficients......Page 300
  Changes in the Technological Coefficients......Page 301
  Changes in the Resources or Right-Hand-Side Values......Page 302
  Excel Solver and Changes in Right-Hand-Side Values......Page 303
 Glossary......Page 305
 Solved Problems......Page 306
 Self-Test......Page 310
 Discussion Questions and Problems......Page 311
 Case Study: Mexicana Wire Works......Page 320
 Case Study: Planning the Product Mix at Panchtantra Corporation......Page 321
 Bibliography......Page 322
8. Linear Programming Applications......Page 324
  Media Selection......Page 325
  Marketing Research......Page 326
  Production Mix......Page 329
  Production Scheduling......Page 330
  Labor Planning......Page 334
  Portfolio Selection......Page 336
  Truck Loading Problem......Page 339
  Diet Problems......Page 341
  Ingredient Mix and Blending Problems......Page 342
 8.7 Other Linear Programming Applications......Page 344
 Self-Test......Page 346
 Problems......Page 347
 Case Study: Cable & Moore......Page 354
 Case Study: Kamdhenu Diary......Page 355
 Bibliography......Page 362
9. Transportation, Assignment, and Network Models......Page 364
 9.1 Introduction......Page 365
  Solving Transportation Problems Using Computer Software......Page 366
  A General LP Model for Transportation Problems......Page 367
  Facility Location Analysis......Page 368
  Linear Program for Assignment Example......Page 371
  Linear Program for Transshipment Example......Page 373
  Example......Page 376
 9.6 Shortest-Route Problem......Page 378
 9.7 All-node-pairs shortest path......Page 379
 9.8 Minimal-Spanning Tree Problem......Page 383
 Glossary......Page 388
 Solved Problems......Page 389
 Self-Test......Page 391
 Discussion Questions and Problems......Page 392
 Case Study: Andrew–Carter, Inc.......Page 405
 Case Study: Northeastern Airlines......Page 406
 Case Study: Southwestern University Traffic Problems......Page 407
 Appendix 9.1: Using QM for Windows......Page 408
10. Integer Programming, Goal Programming, and Nonlinear Programming......Page 410
  Harrison Electric Company Example of Integer Programming......Page 411
  Using Software to Solve the Harrison Integer Programming Problem......Page 413
  Mixed-Integer Programming Problem Example......Page 415
  Capital Budgeting Example......Page 417
  Fixed-Charge Problem Example......Page 419
 10.4 Goal Programming......Page 421
  Example of Goal Programming: Harrison Electric Company Revisited......Page 423
  Ranking Goals with Priority Levels......Page 424
  Goal Programming with Weighted Goals......Page 425
 10.5 Nonlinear Programming......Page 426
  Both Nonlinear Objective Function and Nonlinear Constraints......Page 427
 Summary......Page 429
 Solved Problems......Page 430
 Discussion Questions and Problems......Page 439
 Case Study: Schank Marketing Research......Page 445
 Case Study: Oakton River Bridge......Page 446
 Case Study: Optimizing Crude Oil Logistics at Petrolco......Page 447
 Bibliography......Page 448
11. Project Management......Page 450
 11.1 Introduction......Page 451
  General Foundry Example of PERT/CPM......Page 452
  Activity Times......Page 454
  How to Find the Critical Path......Page 455
  Probability of Project Completion......Page 460
  Using Excel QM for the General Foundry Example......Page 461
  Sensitivity Analysis and Project Management......Page 462
  Planning and Scheduling Project Costs: Budgeting Process......Page 464
  Monitoring and Controlling Project Costs......Page 467
 11.4 Project Crashing......Page 469
  General Foundry Example......Page 470
  Project Crashing with Linear Programming......Page 471
 Summary......Page 474
 Key Equations......Page 475
 Solved Problems......Page 476
 Self-Test......Page 478
 Discussion Questions and Problems......Page 479
 Case Study: Southwestern University Stadium Construction......Page 485
 Case Study: Family Planning Research Center of Nigeria......Page 486
 Bibliography......Page 487
 Appendix 11.1: Project Management with QM for Windows......Page 488
12. Waiting Lines and Queuing Theory Models......Page 490
 12.2 Waiting Line Costs......Page 491
  Three Rivers Shipping Company Example......Page 492
  Waiting Line Characteristics......Page 493
  Identifying Models Using Kendall Notation......Page 494
  Queuing Equations......Page 497
  Arnold’s Muffler Shop Case......Page 498
 12.5 Multichannel Queuing Model with Poisson Arrivals and Exponential Service Times (M/M/m)......Page 502
  Arnold’s Muffler Shop Revisited......Page 503
  Equations for the Constant Service Time Model......Page 505
  Garcia-Golding Recycling, Inc.......Page 506
  Equations for the Finite Population Model......Page 507
  Department of Commerce Example......Page 508
 12.9 More Complex Queuing Models and the Use of Simulation......Page 509
 Glossary......Page 510
 Key Equations......Page 511
 Solved Problems......Page 512
 Self-Test......Page 515
 Discussion Questions and Problems......Page 516
 Case Study: New England Foundry......Page 520
 Bibliography......Page 522
 Appendix 12.1: Using QM for Windows......Page 523
13. Simulation Modeling......Page 524
 13.1 Introduction......Page 525
 13.2 Advantages and Disadvantages of Simulation......Page 526
  Harry’s Auto Tire Example......Page 527
  Using QM for Windows for Simulation......Page 532
  Simulation with Excel Spreadsheets......Page 533
  Simkin’s Hardware Store......Page 535
  Analyzing Simkin’s Inventory Costs......Page 538
  Port of New Orleans......Page 539
  Using Excel to Simulate the Port of New Orleans Queuing Problem......Page 541
  Three Hills Power Company......Page 542
  Cost Analysis of the Simulation......Page 544
  Two Other Types of Simulation Models......Page 547
  Verification and Validation......Page 548
 Glossary......Page 549
 Solved Problems......Page 550
 Self-Test......Page 553
 Discussion Questions and Problems......Page 554
 Case Study: Alabama Airlines......Page 559
 Case Study: Statewide Development Corporation......Page 560
 Case Study: FB Badpoore Aerospace......Page 561
 Case Study: Radiology Department at the Kamala Medical College and Hospital......Page 562
 Bibliography......Page 563
14. Markov Analysis......Page 564
 14.2 States and State Probabilities......Page 565
  The Vector of State Probabilities for Three Grocery Stores Example......Page 566
 14.3 Matrix of Transition Probabilities......Page 567
 14.4 Predicting Future Market Shares......Page 568
 14.5 Markov Analysis of Machine Operations......Page 569
 14.6 Equilibrium Conditions......Page 570
 14.7 Absorbing States and the Fundamental Matrix: Accounts Receivable Application......Page 573
 Summary......Page 577
 Solved Problems......Page 578
 Discussion Questions and Problems......Page 582
 Case Study: Rentall Trucks......Page 587
 Appendix 14.1: Markov Analysis with QM for Windows......Page 588
 Appendix 14.2: Markov Analysis with Excel......Page 590
15. Statistical Quality Control......Page 592
 15.2 Defining Quality and TQM......Page 593
  Variability in the Process......Page 594
  The Central Limit Theorem......Page 596
  Setting x -Chart Limits......Page 597
  Setting Range Chart Limits......Page 600
  p-Charts......Page 601
  c-Charts......Page 603
 Key Equations......Page 605
 Solved Problems......Page 606
 Discussion Questions and Problems......Page 607
 Appendix 15.1: Using QM for Windows for SPC......Page 610
Appendices......Page 612
 Appendix A: Areas Under the Standard Normal Curve......Page 613
 Appendix B: Binomial Probabilities......Page 615
 Appendix C: Values of e−λ for Use in the Poisson Distribution......Page 620
 Appendix D: F Distribution Values......Page 621
 Appendix E: Using POM-QM for Windows......Page 623
 Appendix F: Using Excel QM and Excel Add-Ins......Page 626
 Appendix G: Solutions to Selected Problems......Page 627
 Appendix H: Solutions to Self-Tests......Page 631
Index......Page 634