Spreadsheet Modeling and
Applications,
1e
Albright, Winston
1.
Introduction
to Modeling
1.1.
Introduction
1.2.
A
Waiting-Line Example
1.3.
Modeling
Versus Models
1.4.
The
Seven-Step Modeling Process
1.5.
A Successful
Management Science Application
1.6.
Why Study
Management Science?
1.7.
Software
Included in this Book
1.8.
Conclusion
2.
Introductory
Spreadsheet Modeling
2.1.
Introduction
2.2.
Basic
Spreadsheet Modeling: Concepts and Best Practices
2.3.
Breakeven
Analysis
2.4.
Ordering
with Quantity Discounts and Demand Uncertainty
2.5.
Decisions
Involving the Time Value of Money
2.6.
Conclusion
Appendix:
Tips for Editing and Documenting Spreadsheets
3.
Introduction
to Optimization Modeling
3.1.
Introduction
3.2.
Introduction
to Optimization
3.3.
A
Two-Variable Model
3.4.
Sensitivity
Analysis
3.5.
Properties
of Linear Models
3.6.
Infeasibility
and Unboundedness
3.7.
A Product
Mix Model
3.8.
A Multiperiod Production Model
3.9.
A Comparison
of Algebraic and Spreadsheet Models
3.10.A Decision Support System
3.11.Conclusion
Appendix: Information on Solvers
4.
Linear
Programming Models
4.1.
Introduction
4.2.
Advertising
Models
4.3.
Static Workforce
Scheduling Models
4.4.
Aggregate
Planning Models
4.5.
Blending
Models
4.6.
Production
Process Models
4.7.
Financial
Models
4.8.
Conclusion
5.
Network
Models
5.1.
Introduction
5.2.
Transportation
Models
5.3.
Assignment
Models
5.4.
Minimum Cost
Network Flow Models
5.5.
Shortest
Path Models
5.6.
Project Scheduling
Models
5.7.
Conclusion
6.
Linear
Optimization Models with Integer Variables
6.1.
Introduction
6.2.
Overview of
Optimization with Integer Variables
6.3.
Capital
Budgeting Models
6.4.
Fixed-Cost
Models
6.5.
Set Covering
Models and Location–Assignment Models
6.6.
Conclusion
7.
Nonlinear Optimization
Models
7.1.
Introduction
7.2.
Basic Ideas
of Nonlinear Optimization
7.3.
Pricing
Models
7.4.
Advertising
Response and Selection Models
7.5.
Facility
Location Models
7.6.
Models for
Rating Sports Teams
7.7.
Portfolio
Optimization Models
7.8.
Conclusion
8.
Decision
Making Under Uncertainty
8.1.
Introduction
8.2.
Elements of
a Decision Analysis
8.3.
The
PrecisionTree Add-In
8.4.
Bayes’ Rule
8.5.
Multistage
Decision Problems
8.6.
Incorporating
Attitudes Toward Risk
8.7.
Conclusion
9.
Introduction
to Simulation Modeling
9.1.
Introduction
9.2.
Real
Applications of Simulation
9.3.
Probability
Distributions for Input Variables
9.4.
Simulation
with Built-In Excel Tools
9.5.
Introduction
to @RISK
9.6.
The Effects
of Input Distributions on Results
9.7.
Conclusion
10.
Simulation
Models
10.1.Introduction
10.2.Operations Models
10.3.Financial Models
10.4.Marketing Models
10.5.Simulating Games of Chance
10.6.Conclusion
Appendix:
Creating Histograms with Excel Tools
11.
Queueing
Models
11.1.Introduction
11.2.Elements of Queueing Models
11.3.The Exponential Distribution
11.4.Important Queueing Relationships
11.5.Analytical Queueing Models
11.6.Queueing Simulation Models
11.7.Conclusion
12.
Regression
and Forecasting Models
12.1.Introduction
12.2.Overview of Regression Models
12.3.Simple Regression Models
12.4.Multiple Regression Models
12.5.Overview of Time Series Models
12.6.Moving Averages Models
12.7.Exponential Smoothing Models
12.8.Conclusion
Visit the Cengage site for our books.
Send e-mail to albright@indiana.edu
Albright is retired from the Kelley School of
Business, Indiana University, Bloomington and now works as a
consultant for Palisade Corp.
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Updated: 1/13/2015