You are previewing Management Science: The Art of Modeling with Spreadsheets, 4th Edition.
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Management Science: The Art of Modeling with Spreadsheets, 4th Edition

Book Description

Now in its fourth edition, Powell and Baker's Management Science provides students and business analysts with the technical knowledge and skill needed to develop real expertise in business modeling. In this book, the authors cover spreadsheet engineering, management science, and the modeling craft.

Table of Contents

  1. Cover Page
  2. Title Page
  3. Copyright
  4. Dedication
  5. Brief Contents
  6. Table of Contents
  7. Preface
  8. About the Authors
  9. Chapter 1: Introduction
    1. 1.1 MODELS AND MODELING
    2. 1.2 THE ROLE OF SPREADSHEETS
    3. 1.3 THE REAL WORLD AND THE MODEL WORLD
    4. 1.4 LESSONS FROM EXPERT AND NOVICE MODELERS
    5. 1.5 ORGANIZATION OF THE BOOK
    6. 1.6 SUMMARY
    7. SUGGESTED READINGS
  10. Chapter 2: Modeling in a Problem-Solving Framework
    1. 2.1 INTRODUCTION
    2. 2.2 THE PROBLEM-SOLVING PROCESS
    3. 2.3 INFLUENCE CHARTS
    4. 2.4 CRAFT SKILLS FOR MODELING
    5. 2.5 SUMMARY
    6. SUGGESTED READINGS
    7. EXERCISES
  11. Chapter 3: Spreadsheet Engineering
    1. 3.1 INTRODUCTION
    2. 3.2 DESIGNING A SPREADSHEET
    3. 3.3 DESIGNING A WORKBOOK
    4. 3.4 BUILDING A WORKBOOK
    5. 3.5 TESTING A WORKBOOK
    6. 3.6 SUMMARY
    7. SUGGESTED READINGS
    8. EXERCISES
  12. Chapter 4: Analysis Using Spreadsheets
    1. 4.1 INTRODUCTION
    2. 4.2 BASE-CASE ANALYSIS
    3. 4.3 WHAT-IF ANALYSIS
    4. 4.4 BREAKEVEN ANALYSIS
    5. 4.5 OPTIMIZATION ANALYSIS
    6. 4.6 SIMULATION AND RISK ANALYSIS
    7. 4.7 SUMMARY
    8. EXERCISES
  13. Chapter 5: Data Exploration and Preparation
    1. 5.1 INTRODUCTION
    2. 5.2 DATABASE STRUCTURE
    3. 5.3 TYPES OF DATA
    4. 5.4 DATA EXPLORATION
    5. 5.5 SUMMARY
    6. SUGGESTED READINGS
    7. EXERCISES
    8. APPENDIX 5.1 DATA PREPARATION
    9. A.5.1 HANDLING MISSING DATA
    10. A.5.2 BINNING CONTINUOUS DATA
    11. A.5.3 TRANSFORMING CATEGORICAL DATA
    12. A.5.4 FUNCTIONAL TRANSFORMATIONS
    13. A.5.5 NORMALIZATIONS
  14. Chapter 6: Classification and Prediction Methods
    1. 6.1 INTRODUCTION
    2. 6.2 PRELIMINARIES
    3. 6.3 THE K-NEAREST NEIGHBOR METHOD
    4. 6.4 THE NAïVE BAYES METHOD
    5. 6.5 CLASSIFICATION AND PREDICTION TREES
    6. 6.6 MULTIPLE LINEAR REGRESSION
    7. 6.7 LOGISTIC REGRESSION
    8. 6.8 NEURAL NETWORKS
    9. 6.9 SUMMARY
    10. SUGGESTED READINGS
    11. EXERCISES
  15. Chapter 7: Short-Term Forecasting
    1. 7.1 INTRODUCTION
    2. 7.2 FORECASTING WITH TIME-SERIES MODELS
    3. 7.3 THE EXPONENTIAL SMOOTHING MODEL
    4. 7.4 EXPONENTIAL SMOOTHING WITH A TREND
    5. 7.5 EXPONENTIAL SMOOTHING WITH TREND AND CYCLICAL FACTORS
    6. 7.6 USING XLMiner FOR SHORT-TERM FORECASTING
    7. 7.7 SUMMARY
    8. SUGGESTED READINGS
    9. EXERCISES
  16. Chapter 8: Nonlinear Optimization
    1. 8.1 INTRODUCTION
    2. 8.2 AN OPTIMIZATION EXAMPLE
    3. 8.3 BUILDING MODELS FOR SOLVER
    4. 8.4 MODEL CLASSIFICATION AND THE NONLINEAR SOLVER
    5. 8.5 NONLINEAR PROGRAMMING EXAMPLES
    6. 8.6 SENSITIVITY ANALYSIS FOR NONLINEAR PROGRAMS
    7. 8.7 THE PORTFOLIO OPTIMIZATION MODEL
    8. 8.8 SUMMARY
    9. SUGGESTED READINGS
    10. EXERCISES
  17. Chapter 9: Linear Optimization
    1. 9.1 INTRODUCTION
    2. 9.2 ALLOCATION MODELS
    3. 9.3 COVERING MODELS
    4. 9.4 BLENDING MODELS
    5. 9.5 SENSITIVITY ANALYSIS FOR LINEAR PROGRAMS
    6. 9.6 PATTERNS IN LINEAR PROGRAMMING SOLUTIONS
    7. 9.7 DATA ENVELOPMENT ANALYSIS
    8. 9.8 SUMMARY
    9. SUGGESTED READINGS
    10. EXERCISES
    11. APPENDIX 9.1 THE SOLVER SENSITIVITY REPORT
  18. Chapter 10: Optimization of Network Models
    1. 10.1 INTRODUCTION
    2. 10.2 THE TRANSPORTATION MODEL
    3. 10.3 ASSIGNMENT MODEL
    4. 10.4 THE TRANSSHIPMENT MODEL
    5. 10.5 A STANDARD FORM FOR NETWORK MODELS
    6. 10.6 NETWORK MODELS WITH YIELDS
    7. 10.7 NETWORK MODELS FOR PROCESS TECHNOLOGIES
    8. 10.8 SUMMARY
    9. EXERCISES
  19. Chapter 11: Integer Optimization
    1. 11.1 INTRODUCTION
    2. 11.2 INTEGER VARIABLES AND THE INTEGER SOLVER
    3. 11.3 BINARY VARIABLES AND BINARY CHOICE MODELS
    4. 11.4 BINARY VARIABLES AND LOGICAL RELATIONSHIPS
    5. 11.5 THE FACILITY LOCATION MODEL
    6. 11.6 SUMMARY
    7. SUGGESTED READINGS
    8. EXERCISES
  20. Chapter 12: Optimization of Nonsmooth Models
    1. 12.1 INTRODUCTION
    2. 12.2 FEATURES OF THE EVOLUTIONARY SOLVER
    3. 12.3 CURVE FITTING (REVISITED)
    4. 12.4 THE ADVERTISING BUDGET PROBLEM (REVISITED)
    5. 12.5 THE CAPITAL BUDGETING PROBLEM (REVISITED)
    6. 12.6 THE FIXED COST PROBLEM (REVISITED)
    7. 12.7 THE MACHINE-SEQUENCING PROBLEM
    8. 12.8 THE TRAVELING SALESPERSON PROBLEM
    9. 12.9 GROUP ASSIGNMENT
    10. 12.10 SUMMARY
    11. EXERCISES
  21. Chapter 13: Decision Analysis
    1. 13.1 INTRODUCTION
    2. 13.2 PAYOFF TABLES AND DECISION CRITERIA
    3. 13.3 USING TREES TO MODEL DECISIONS
    4. 13.4 USING DECISION TREE SOFTWARE
    5. 13.5 MAXIMIZING EXPECTED UTILITY WITH DECISION TREE
    6. 13.6 SUMMARY
    7. SUGGESTED READINGS
    8. EXERCISES
  22. Chapter 14: Monte Carlo Simulation
    1. 14.1 INTRODUCTION
    2. 14.2 A SIMPLE ILLUSTRATION
    3. 14.3 THE SIMULATION PROCESS
    4. 14.4 CORPORATE VALUATION USING SIMULATION
    5. 14.5 OPTION PRICING USING SIMULATION
    6. 14.6 SELECTING UNCERTAIN PARAMETERS
    7. 14.7 SELECTING PROBABILITY DISTRIBUTIONS
    8. 14.8 ENSURING PRECISION IN OUTPUTS
    9. 14.9 INTERPRETING SIMULATION OUTCOMES
    10. 14.10 WHEN TO SIMULATE AND WHEN NOT TO SIMULATE
    11. 14.11 SUMMARY
    12. SUGGESTED READINGS
    13. EXERCISES
  23. Chapter 15: Optimization in Simulation
    1. 15.1 INTRODUCTION
    2. 15.2 OPTIMIZATION WITH ONE OR TWO DECISION VARIABLES
    3. 15.3 STOCHASTIC OPTIMIZATION
    4. 15.4 CHANCE CONSTRAINTS
    5. 15.5 TWO-STAGE PROBLEMS WITH RECOURSE
    6. 15.6 SUMMARY
    7. SUGGESTED READINGS
    8. EXERCISES
    9. Modeling Cases
  24. Appendix 1: Basic Excel Skills
    1. INTRODUCTION
    2. EXCEL PREREQUISITES
    3. THE EXCEL WINDOW
    4. CONFIGURING EXCEL
    5. MANIPULATING WINDOWS AND SHEETS
    6. NAVIGATION
    7. SELECTING CELLS
    8. ENTERING TEXT AND DATA
    9. EDITING CELLS
    10. FORMATTING
    11. BASIC FORMULAS
    12. BASIC FUNCTIONS
    13. CHARTING
    14. PRINTING
    15. HELP OPTIONS
    16. KEYBOARD SHORTCUTS
    17. CELL COMMENTS
    18. NAMING CELLS AND RANGES
    19. SOME ADVANCED TOOLS
  25. Appendix 2: Macros and VBA
    1. INTRODUCTION
    2. RECORDING A MACRO
    3. EDITING A MACRO
    4. CREATING A USER-DEFINED FUNCTION
    5. SUGGESTED READINGS
  26. Appendix 3: Basic Probability Concepts
    1. INTRODUCTION
    2. PROBABILITY DISTRIBUTIONS
    3. EXAMPLES OF DISCRETE DISTRIBUTIONS
    4. EXAMPLES OF CONTINUOUS DISTRIBUTIONS
    5. EXPECTED VALUES
    6. CUMULATIVE DISTRIBUTION FUNCTIONS
    7. TAIL PROBABILITIES
    8. VARIABILITY
    9. SAMPLING
  27. Index