Management science: the art of modeling with spreadsheets ; [compatible with Excel 2010 ; featuring risk solver platform]
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| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Hoboken, NJ
Wiley
2009
|
| Edition: | 3. ed. |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XIII, 511 S. graph. Darst. |
| ISBN: | 9780470530672 |
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| 245 | 1 | 0 | |a Management science |b the art of modeling with spreadsheets ; [compatible with Excel 2010 ; featuring risk solver platform] |c Stephen G. Powell ; Kenneth R. Baker |
| 250 | |a 3. ed. | ||
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Record in the Search Index
| _version_ | 1804143245119193088 |
|---|---|
| adam_text | Titel: Management science
Autor: Powell, Stephen G.
Jahr: 2009
Table of Contents
PREFACE IX CHAPTER 3 BASIC EXCEL SKILLS 52
ABOUT THE AUTHORS Xlll
chapter 1 INTRODUCTION 1
3.1 Introduction 52
3.2 Excel Prerequisites 52
3.3 The Excel Window 53
3.4 Configuring Excel 55
1.1 Models And Modeling i 3.5 Manipulating Windows and Sheets 57
1.1.1 Why Study Modeling? 2 3.6 Navigation 57
1.1.2 Models in Business 2 3.7 Selecting Cells 59
1.1.3 Models in Business Education 3 3.8 Entering Text and Data 59
1.1.4 Benefits of Business Models 4 3.9 Editing Cells 60
1.2 The Role of Spreadsheets 4 3.10 Formatting 61
1.2.1 Risks of Spreadsheet Use 5 3.11 Basic Formulas 62
1.2.2 Challenges for Spreadsheet Users 6 3.12 Basic Functions 63
1.2.3 Background Knowledge for Spreadsheet 3.13 Charting 67
Modeling 8 3.14 Printing 70
1.3 The Real World and the Model World 8 3.15 Help Options 71
1.4 Lessons From Expert and Novice Modelers 10 3.16 Summary 71
1.4.1 Expert Modelers 11 Suggested Readings 72
1.4.2 Novice Modelers 12
1.5 Organization of the Book 14 chapter 4 ADVANCED EXCEL SKILLS 73
1.6 Summary 15 41 Introduction 73
Suggested Readings 15 42 Keyboard shortcuts 73
chapter 2 MODELING IN A PROBLEM-SOLVING 43 Controls 74
FRAMEWORK 16 ________ 4A Cell Comments 77
---------------------------------------------------------------------------4.5 Naming Cells and Ranges 78
2.1 Introduction 16 4.6 Advanced Formulas and Functions 80
2.2 The Problem-Solving Process 17 4.6.1 R1C1 Reference Style 81
2.2.1 Some Key Terms 18 4.6.2 Mixed Addresses 81
2.2.2 The Six-Stage Problem-Solving Process 19 4.6.3 Nesting Calculations 82
2.2.3 Mental Models and Formal Models 25 4.6.4 Parameterization 83
2.3 Influence Charts 26 4.6.5 Advanced Functions 84
2.3.1 A First Example 27 4.7* Recording Macros and Using VBA 88
2.3.2 An Income Statement as an Influence Chart 29 4.7.1 Recording a Macro 88
2.3.3 Principles for Building Influence Charts 30 4.7.2 Editing a Macro 90
2.3.4 Two Additional Examples 30 4.7.3 Creating a User-Defined Function 93
2.4 Craft Skills for Modeling 34 4.8 Summary 94
2.4.1 Simplify the Problem 36 Suggested Readings 94
2.4.2 Break the Problem into Modules 37
2.4.3 Build a Prototype and Refine It 38 chapter 5 SPREADSHEET ENGINEERING 95
2.4.4 Sketch Graphs of Key Relationships 41
2.4.5 Identify Parameters and Perform Sensitivity 51 Introduction 95
Analysis 43 Designing a Spreadsheet 97
2.4.6 Separate the Creation of Ideas from Their 52-1 Sketch the Spreadsheet 97
Evaluation 45 •5-2-2 Organize the Spreadsheet into Modules 98
2.4.7 Work Backward from the Desired Answer 46 5-2-3 Start Small 99
2.4.8 Focus on Model Structure, not on Data 52A Isolate Input Parameters 100
Collection 46 5-2-5 Design for Use 100
2.5 Summary 49 5-2-6 Keep It Simple 101
Suggested Readings so 5-2-7 Design for Communication 101
Exercises 50 5.2.8 Document Important Data and Formulas 102
5.3 Designing a Workbook 103 7.6 Summary 156
5.3.1 Use Separate Worksheets to Group Similar Suggested Readings 156
Kinds of Information 104 Exercises 156
5.3.2 Design Workbooks for Ease of Navigation
and Use 105 chapters REGRESSION ANALYSIS 159_________
5.3.3 Design a Workbook as a Decision-Support Introduction 159
System 107 A Decision-Making Example 160
5.4 Building a Workbook 109 821 Base-case Analysis 160
5.4.1 Follow a Plan 109 822 Sensitivity Analysis 161
5.4.2 Build One Worksheet or Module at a 823 Base-case Summary 163
Time 109 3 Exploring Data: Scatter Plots and Correlation 163
5.4.3 Predict the Outcome of Each Formula 109 4 simple Linear Regression 165
5.4.4 Copy and Paste Formulas Carefully 109 5 Goodness-of-Fit 166
5.4.5 Use Relative and Absolute Addressing to 6 simple Regression in the BPI Example 170
Simplify Copying 110 87 Simple Nonlinear Regression 173
5.4.6 Use the Function Wizard to Ensure Correct Multiple Linear Regression 174
Syntax 110 89 Multiple Regression in the BPI Example 176
5.4.7 Use Range Names to Make Formulas Easy to 810 Regression Assumptions 178
Read 110 8.11* Using the Excel Tools Trendline and LINEST 179
5.4.8 Choose Input Data to Make Errors Stand 8111 Trendline 179
8.11.2 LINEST 181
5.5 Testing a Workbook gu Summary 182
5.5.1 Check That Numerical Results Look Suggested Readings 183
Plausible 112 Exercises 183
5.5.2 Check That Formulas Are Correct 112
5.5.3 Test That Model Performance Is
... chapter 9 SHORT-TERM FORECASTING 186
Plausible 116 ------------------------------------------------------------------------
5.6 Summary 116 9.1 Introduction 186
Suggested Readings 117 9.2 Forecasting with Time-Series Models 186
Exercises 117 9.2.1 The Moving-Average Model 187
9.2.2 Measures of Forecast Accuracy 190
chapter 6 ANALYSIS USING 93 The Exponential Smoothing Model 191
SPREADSHEETS 119 9.4 Exponential Smoothing with a Trend 195
9.5 Exponential Smoothing with Trend and Cyclical
6.1 Introduction 119 Factors 199
6.2 Base-Case Analysis 120 9.6 Summary 202
6.3 What-If Analysis 120 Suggested Readings 202
6.3.1 Benchmarking 122 Exercises 202
6.3.2 Scenarios 123
6.3.3 Parametric Sensitivity 125 chapter 10 NONLINEAR OPTIMIZATION 206
6.3.4 Tornado Charts 129
6.4 Breakeven Analysis 130 10.1 Introduction 206
6.5 Optimization Analysis 132 10.2 An Optimization Example 207
6.6 Simulation and Risk Analysis 132 10.2.1 Optimizing Ql 207
6.7 Summary 134 10.2.2 Optimization Over All Four Quarters 210
Exercises 134 10.2.3 Incorporating the Budget Constraint 211
10.3 Building Models for Solver 213
chapter 7 DATA ANALYSIS FOR formUtlation 213
MODELING 137________________________________ Layout 215
---------------------------------------------------------------- 10.3.3 Interpreting Results 216
7.1 Introduction 137 10.4 Model Classification and the Nonlinear
7.2 Finding Facts from Databases 138 Solver 216
7.2.1 Searching and Editing 140 10-5 Nonlinear Programming Examples 218
7.2.2 Sorting 141 10.5.1 Facility Location 218
7.2.3 Filtering 143 10.5.2 Revenue Maximization 220
7.2.4 Tabulating 145 10.5.3 Curve Fitting 222
7.3 Analyzing Sample Data 148 10-5.4 Economic Order Quantity 225
7.4 Estimating Parameters: Point Estimates 150 10-6 Sensitivity Analysis for Nonlinear Programs 227
7.5 Estimating Parameters: Interval Estimates 151 10-7* The Portfolio Optimization Model 232
7.5.1 Interval Estimates for the Mean 152 10.8 Summary 235
7.5.2 Interval Estimates for a Proportion 155 Suggested Readings 235
7.5.3 Sample-Size Determination 155 Exercises 236
chapter 11 LINEAR OPTIMIZATION 240________ chapter 13 INTEGER OPTIMIZATION 314_______
11.1 Introduction 240 13.1 Introduction 314
11.1.1 Linearity 240 13.2 Integer Variables and the Integer Solver 315
11.1.2 Simplex Algorithm 241 13.3 Binary Variables and Binary Choice Models 317
11.2 Allocation Models 242 13.3.1 The Capital Budgeting Problem 317
11.2.1 Formulation 243 13.3.2 The Set Covering Problem 320
11.2.2 Spreadsheet Model 243 13.4 Binary Variables and Logical Relationships 322
11.2.3 Optimization 245 13.4.1 Relationships Among Projects 322
11.3 Covering Models 247 13.4.2 Linking Constraints and Fixed Costs 324
11.3.1 Formulation 247 13.4.3 Threshold Levels and Quantity
11.3.2 Spreadsheet Model 248 Discounts 327
11.3.3 Optimization 249 13.5* The Facility Location Model 329
11.4 Blending Models 250 13.5.1 The Capacitated Problem 330
11.4.1 Blending Constraints 250 13.5.2 The Uncapacitated Problem 332
11.4.2 Formulation 252 13.5.3 The Assortment Model 334
11.4.3 Spreadsheet Model 253 13.6 Summary 335
11.4.4 Optimization 254 Suggested Readings 336
11.5 Sensitivity Analysis for Linear Programs 255 Exercises 336
11.5.1 Sensitivity to Objective Function
Coefficients 255 chapters OPTIMIZATION OF NON-SMOOTH
11.5.2 Sensitivity to Constraint Constants 257 MODFT 9
11.6 Patterns in Linear Programming Solutions 260
11.6.1 Identifying Patterns 260 14.1 Introduction 340
11.6.2 Further Examples 262 14.2 Features of the Evolutionary Solver 340
11.6.3 Review 267 14.3 An Illustrative Example: Nonlinear Regression 341
11.7* Data Envelopment Analysis 268 14.4 The Advertising Budget Problem (Revisited) 348
11.8 Summary 272 14.5 The Capital Budgeting Problem (Revisited) 350
Suggested Readings 273 14.6 The Fixed Cost Problem (Revisited) 352
Exercises 273 14.7 The Machine-Sequencing Problem 353
Appendix 11.1 The Solver Sensitivity Report 278 14.8 The Traveling Salesperson Problem 356
14.9 Group Assignment 358
chapter 12 OPTIMIZATION OF NETWORK 14.10 Summary 361
MODELS 281__________________________________ Exercises 361
12.1 Introduction 281
12.2 The Transportation Model 281 chapter is DECISION ANALYSIS 365___________
15.1 Introduction 365
12.2.1 Flow Diagram 282
1223 Spreadsh^eTModel 228832 152 Payoff Tables and Decision Criteria 366
12.2.4 Optimization 284 .2.1 Benchmark Criteria 366
12.2.5 Modifications to the Model 285 .2.2 Incorporating Probabilities 368
12.2.6 Sensitivity Analysis 286 153 Using Trees to Model Decisions 369
15.3.1 Decision Trees 370
12.3 Assignment Model 290
12.3.1 Model Formulation 291
15.3.2 Decision Trees for a Series of Decisions 373
12.3.2 Spreadsheet Model 292 15-3-3 Principles for Building and Analyzing
12.3.3 Optimization 292
12.3.4 Sensitivity Analysis 292 5.3.4 The Cost of Uncertamty 377
12.4 The Transshipment Model 293 l5A ^ff decision Tree Software 378
12.4.1 Formulation 294 15A1 Solvm8 a SimPle ExamPle Wlth Decisl0n
12.4.2 Spreadsheet Model 295 Tree 379
12.4.3 Optimization 296 .4.2 Sensitivity Analysis with Decision Tree 382
12.4.4 Sensitivity Analysis 297 15A3 Minimizing Expected Cost with Decision
12.5 A Standard Form for Network Models 297
12.6 Network Models with Yields 300 15.5* Maximizing Expected Utuity with Decision Tree 383
12.6.1 Yields as Reductions in Flow 300 15 6 nummary 387
12.6.2 Yields as Expansions in Flow 301 Suggested Readings 388
12.6.3 Patterns in General Network Models 304 Exercises 388
12.7* Network Models for Process Technologies 305
12.7.1 Formulation 306 chapter 16 MONTE CARLO SIMULATION 392
12.7.2 Spreadsheet Model 308
12.7.3 Optimization 308 161 Introduction 392
12.8 Summary 309 16-2 A Simple Illustration 393
Exercises 309 16-3 The Simulation Process 395
16.3.1 Base-Case Model 396 17.2.2 Grid Search 451
16.3.2 Sensitivity Analysis 398 17.2.3 Optimizing using Simulation Sensitivity 453
16.3.3 Specifying Probability Distributions 399 17.2.4 Optimizing Using Solver 455
16.3.4 Specifying Outputs 400 17.3 Stochastic Optimization 456
16.3.5 Setting Simulation Parameters 401 17.3.1 Optimization of the Base-Case Model 456
16.3.6 Analyzing Simulation Outputs 401 17.3.2 A Portfolio Optimization Problem 458
16.4 Corporate Valuation Using Simulation 405 17.4 Chance Constraints 461
16.4.1 Base-Case Model 406 17.5 Two-Stage Problems with Recourse 467
16.4.2 Sensitivity Analysis 408 17.6 Summary 472
16.4.3 Selecting Probability Distributions 409 Suggested Readings 472
16.4.4 Simulation Analysis 410 Exercises 472
16.4.5 Simulation Sensitivity 412
16.5 Option Pricing Using Simulation 415 MODELING CASES 478
16.5.1 The Logic of Options 415 Retirement Planning 478
16.5.2 Modeling Stock Prices 416 Draft TV Commercials 479
16.5.3 Pricing an Option 419 Icebergs for Kuwait 479
16.5.4 Sensitivity to Volatility 420 The Racquetball Racket 480
16.5.5 Simulation Precision 421 The XYZ Company 481
16.6 Seecting Uncertain Parameters 421 Medical Supplies for Banjul 482
16.7 Selecting Probabihty Distributions 424 Reid s Raisin Company 482
16.7.1 Empirical Data and Judgmental Data 424 The Big Rig Truck Rental Company 483
16.7.2 Six Essential Distributions 425 Flexible Insurance Coverage 483
16.7.3 Fitting Distributions to Data 430 Snoey Software Company 484
16.8 Ensuring Precision in Outputs 432 Cox Cable and Wire Company 484
16.8.1 Illustrations of Simulation Error 432 The BMW Company 486
16.8.2 Precision versus Accuracy 434 The ERP Decision 487
16.8.3 An Expenmental Method 436 National Leasing, Inc. 490
16.8.4 Precision Using the MSE 435 Mega Pharma and Micro Pharma 492
16.8.5 Simulation Error in a Decision Context 436
16.9 InterpretingSimulation_ Outcomes 437 APPENDIX: BASIC PROBABILITY CONCEPTS 494
16.9.1 Simulation Results 437
16.9.2 Displaying Results on the Spreadsheet 438 Introduction 494
16.10* When to Simulate and When Not to Simulate 440 Probability Distributions 494
16.11 Summary 442 Examples of Discrete Distributions 497
Suggested Readings 443 Examples of Continuous Distributions 498
Exercises 443 Expected Values 499
Cumulative Distribution Functions 501
chapter 17 OPTIMIZATION IN SIMULATION 448 Tail Probabilities 501
Variability 602
17.1 Introduction 448 Sampling Theory 503
17.2 Optimization with One or Two Decision
Variables 448
17.2.1 Base-case Model 449 INDEX 505
|
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| author | Powell, Stephen G. Baker, Kenneth R. |
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| classification_rvk | QH 470 |
| ctrlnum | (OCoLC)705761250 (DE-599)BVBBV036631257 |
| discipline | Wirtschaftswissenschaften |
| edition | 3. ed. |
| format | Book |
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| id | DE-604.BV036631257 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T22:44:35Z |
| institution | BVB |
| isbn | 9780470530672 |
| language | English |
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| owner_facet | DE-M347 DE-898 DE-BY-UBR |
| physical | XIII, 511 S. graph. Darst. |
| publishDate | 2009 |
| publishDateSearch | 2009 |
| publishDateSort | 2009 |
| publisher | Wiley |
| record_format | marc |
| spelling | Powell, Stephen G. Verfasser aut Management science the art of modeling with spreadsheets ; [compatible with Excel 2010 ; featuring risk solver platform] Stephen G. Powell ; Kenneth R. Baker 3. ed. Hoboken, NJ Wiley 2009 XIII, 511 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier aBusiness xComputer simulation aElectronic spreadsheets Tabellenkalkulation (DE-588)4117161-5 gnd rswk-swf Entscheidungsfindung (DE-588)4113446-1 gnd rswk-swf Prozessanalyse (DE-588)4136607-4 gnd rswk-swf Unternehmensplanung (DE-588)4078609-2 gnd rswk-swf Computersimulation (DE-588)4148259-1 gnd rswk-swf Unternehmensplanung (DE-588)4078609-2 s Entscheidungsfindung (DE-588)4113446-1 s Computersimulation (DE-588)4148259-1 s Tabellenkalkulation (DE-588)4117161-5 s DE-604 Prozessanalyse (DE-588)4136607-4 s 1\p DE-604 Baker, Kenneth R. Verfasser aut HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020551066&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Powell, Stephen G. Baker, Kenneth R. Management science the art of modeling with spreadsheets ; [compatible with Excel 2010 ; featuring risk solver platform] aBusiness xComputer simulation aElectronic spreadsheets Tabellenkalkulation (DE-588)4117161-5 gnd Entscheidungsfindung (DE-588)4113446-1 gnd Prozessanalyse (DE-588)4136607-4 gnd Unternehmensplanung (DE-588)4078609-2 gnd Computersimulation (DE-588)4148259-1 gnd |
| subject_GND | (DE-588)4117161-5 (DE-588)4113446-1 (DE-588)4136607-4 (DE-588)4078609-2 (DE-588)4148259-1 |
| title | Management science the art of modeling with spreadsheets ; [compatible with Excel 2010 ; featuring risk solver platform] |
| title_auth | Management science the art of modeling with spreadsheets ; [compatible with Excel 2010 ; featuring risk solver platform] |
| title_exact_search | Management science the art of modeling with spreadsheets ; [compatible with Excel 2010 ; featuring risk solver platform] |
| title_full | Management science the art of modeling with spreadsheets ; [compatible with Excel 2010 ; featuring risk solver platform] Stephen G. Powell ; Kenneth R. Baker |
| title_fullStr | Management science the art of modeling with spreadsheets ; [compatible with Excel 2010 ; featuring risk solver platform] Stephen G. Powell ; Kenneth R. Baker |
| title_full_unstemmed | Management science the art of modeling with spreadsheets ; [compatible with Excel 2010 ; featuring risk solver platform] Stephen G. Powell ; Kenneth R. Baker |
| title_short | Management science |
| title_sort | management science the art of modeling with spreadsheets compatible with excel 2010 featuring risk solver platform |
| title_sub | the art of modeling with spreadsheets ; [compatible with Excel 2010 ; featuring risk solver platform] |
| topic | aBusiness xComputer simulation aElectronic spreadsheets Tabellenkalkulation (DE-588)4117161-5 gnd Entscheidungsfindung (DE-588)4113446-1 gnd Prozessanalyse (DE-588)4136607-4 gnd Unternehmensplanung (DE-588)4078609-2 gnd Computersimulation (DE-588)4148259-1 gnd |
| topic_facet | aBusiness xComputer simulation aElectronic spreadsheets Tabellenkalkulation Entscheidungsfindung Prozessanalyse Unternehmensplanung Computersimulation |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020551066&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT powellstepheng managementsciencetheartofmodelingwithspreadsheetscompatiblewithexcel2010featuringrisksolverplatform AT bakerkennethr managementsciencetheartofmodelingwithspreadsheetscompatiblewithexcel2010featuringrisksolverplatform |