1. Introduction to Modeling and Decision Analysis
Introduction
The Modeling Approach to Decision Making
Characteristics and Benefits of Modeling
Mathematical Models
Categories of Mathematical Models
Business Analytics and the Problem-Solving Process
Anchoring and Framing Effects
Good Decisions vs. Good Outcomes
Summary
References
Questions and Problems
Case
2. Introduction to Optimization and Linear Programming
Introduction
Applications of Mathematical Optimization
Characteristics of Optimization Problems
Expressing Optimization Problems Mathematically
Mathematical Programming Techniques
An Example LP Problem
Formulating LP Models
Summary of the LP Model for the Example Problem
The General Form of an LP Model
Solving LP Problems: An Intuitive Approach
Solving LP Problems: A Graphical Approach
Special Conditions in LP Models
Summary
References
Questions and Problems
Case
3. Modeling and Solving LP Problems in a Spreadsheet
Introduction
Spreadsheet Solvers
Solving LP Problems in a Spreadsheet
The Steps in Implementing an LP Model in a Spreadsheet
A Spreadsheet Model for the Blue Ridge Hot Tubs Problem
How Solver Views the Model
Using Analytic Solver Platform
Using Excel’s Built-in Solver
Goals and Guidelines for Spreadsheet Design
Make vs. Buy Decisions
An Investment Problem
A Transportation Problem
A Blending Problem
A Production and Inventory Planning Problem
A Multiperiod Cash Flow Problem
Data Envelopment Analysis
Summary
References
Questions and Problems
Case
4. Sensitivity Analysis and the Simplex Method
Introduction
The Purpose of Sensitivity Analysis
Approaches to Sensitivity Analysis
An Example Problem
The Answer Report
The Sensitivity Report
The Limits Report
Ad Hoc Sensitivity Analysis
Robust Optimization
The Simplex Method
Summary
References
Questions and Problems
Case
5. Network Modeling
Introduction
The Transshipment Problem
The Shortest Path Problem
The Equipment Replacement Problem
Transportation/Assignment Problems
Generalized Network Flow Problems
Maximal Flow Problems
Special Modeling Considerations
Minimal Spanning Tree Problems
Summary
References
Questions and Problems
Case
6. Integer Linear Programming
Introduction
Integrality Conditions
Relaxation
Solving the Relaxed Problem
Bounds
Rounding
Stopping Rules
Solving ILP Problems Using Solver
Other ILP Problems
An Employee Scheduling Problem
Binary Variables
A Capital Budgeting Problem
Binary Variables and Logical Conditions
The Line Balancing Problem
The Fixed-Charge Problem
Minimum Order/Purchase Size
Quantity Discounts
A Contract Award Problem
The Branch-and-Bound Algorithm (Optional)
Summary
References
Questions and Problems
Case
7. Goal Programming and Multiple Objective Optimization
Introduction
Goal Programming
A Goal Programming Example
Comments about Goal Programming
Multiple Objective Optimization
An MOLP Example
Comments on MOLP
Summary
References
Questions and Problems
Case
8. Nonlinear Programming & Evolutionary Optimization
Introduction
The Nature of NLP Problems
Solution Strategies for NLP Problems
Local vs. Global Optimal Solutions
Economic Order Quantity Models
Location Problems
Nonlinear Network Flow Problem
Project Selection Problems
Optimizing Existing Financial Spreadsheet Models
The Portfolio Selection Problem
Sensitivity Analysis
Solver Options for Solving NLPs
Evolutionary Algorithms
Forming Fair Teams
The Traveling Salesperson Problem
Summary
References
Questions and Problems
Case
9. Regression Analysis
Introduction
An Example
Regression Models
Simple Linear Regression Analysis
Defining “Best Fit”
Solving the Problem Using Solver
Solving the Problem Using the Regression Tool
Evaluating the Fit
The R2 Statistic
Making Predictions
Statistical Tests for Population Parameters
Introduction to Multiple Regression
A Multiple Regression Example
Selecting the Model
Making Predictions
Binary Independent Variables
Statistical Tests for the Population Parameters
Polynomial Regression
Summary
References
Questions and Problems
Case
10. Data Mining
Introduction
Data Mining Overview
Classification
Discriminant Analysis
Logistic Regression
k-Nearest Neighbor
Classification Trees
Neural Networks
Naïve Bayes
Comments on Classification
Prediction
Association Rules (Affinity Analysis)
Cluster Analysis
Time Series
Summary
References
Questions and Problems
Case
11. Time Series Forecasting
Introduction
Time Series Methods
Measuring Accuracy
Stationary Models
Moving Averages
Weighted Moving Averages
Exponential Smoothing
Seasonality
Stationary Data with Additive Seasonal Effects
Stationary Data with Multiplicative Seasonal Effects
Trend Models
Double Moving Average
Double Exponential Smoothing (Holt’s Method)
Holt-Winter’s Method for Additive Seasonal Effects
Holt-Winter’s Method for Multiplicative Seasonal Effects
Modeling Time Series Trends Using Regression
Linear Trend Model
Quadratic Trend Model
Modeling Seasonality with Regression Models
Adjusting Trend Predictions with Seasonal Indices
Seasonal Regression Models
Combining Forecasts
Summary
References
Questions and Problems
Case
12. Introduction to Simulation Using Analytic Solver Platform
Introduction
Random Variables and Risk
Why Analyze Risk?
Methods of Risk Analysis
A Corporate Health Insurance Example
Spreadsheet Simulation Using Analytic Solver Platform
Random Number Generators
Preparing the Model for Simulation
Running the Simulation
Data Analysis
The Uncertainty of Sampling
Interactive Simulation
The Benefits of Simulation
Additional Uses of Simulation
A Reservation Management Example
An Inventory Control Example
A Project Selection Example
A Portfolio Optimization Example
Summary
References
Questions and Problems
Case
13. Queuing Theory
Introduction
The Purpose of Queuing Models
Queuing System Configurations
Characteristics of Queuing Systems
Kendall Notation
Queuing Models
The M/M/s Model
The M/M/s Model with Finite Queue Length
The M/M/s Model with Finite Population
The M/G/1 Model
The M/D/1 Model
Simulating Queues and the Steady-State Assumption
Summary
References
Questions and Problems
Case
14. Decision Analysis
Introduction
Good Decisions vs. Good Outcomes
Characteristics of Decision Problems
An Example
The Payoff Matrix
Decision Rules
Nonprobabilistic Methods
Probabilistic Methods
The Expected Value of Perfect Information
Decision Trees
Creating Decision Trees with Analytic Solver Platform
Multistage Decision Problems
Sensitivity Analysis
Using Sample Information in Decision Making
Computing Conditional Probabilities
Utility Theory
Multicriteria Decision Making
The Multicriteria Scoring Model
The Analytic Hierarchy Process
Summary
References
Questions and Problems
Case
