Solutions Manual to Accompany
An Introduction To
Management Science
Quantitative Approaches
To Decision Making
Twelfth Edition
David R. Anderson
University of Cincinnati
Dennis J. Sweeney
University of Cincinnati
Thomas A. Williams
Rochester Institute of Technology
South-Western
Cincinnati, Ohio
This edition is intended for use outside of the U.S. only, with content that may be different from the U.S. Edition. This may not be resold, copied,
or distributed without the prior consent of the publisher.
, Contents
Preface
Chapter
1. Introduction
2. An Introduction to Linear Programming
3. Linear Programming: Sensitivity Analysis and Interpretation of Solution
4. Linear Programming Applications
5. Linear Programming: The Simplex Method
6. Simplex-Based Sensitivity Analysis and Duality
7. Transportation, Assignment and Transshipment Problems
8. Integer Linear Programming
9. Network Models
10. Project Scheduling: PERT/CPM
11. Inventory Models
12. Waiting Line Models
13. Simulation
14. Decision Analysis
15. Multicriteria Decision Problems
16. Forecasting
17. Markov Processes
18. Dynamic Programming
This edition is intended for use outside of the U.S. only, with content that may be different from the U.S. Edition. This may not be resold, copied,
or distributed without the prior consent of the publisher.
, Preface
The purpose of An Introduction to Management Science is to provide students with a sound
conceptual understanding of the role management science pays in the decision-making
process. The text emphasizes the application of management science by using problem
situations to introduce each of the management science concepts and techniques. The book
has been specifically designed to meet the needs of nonmathematicians who are studying
business and economics.
The Solutions Manual furnishes assistance by identifying learning objectives and providing
detailed solutions for all exercises in the text.
Note: The solutions to the case problems are included in the Solutions to Case Problems
Manual.
Acknowledgements
We would like to provide a special acknowledgement to Catherine J. Williams for her
efforts in preparing the pages for the Solutions Manual. We are also indebted to our
acquisitions editor Charles E. McCormick, Jr. and our developmental editor Alice C. Denny
for their support during the preparation of this manual.
David R. Anderson
Dennis J. Sweeney
Thomas A. Williams
This edition is intended for use outside of the U.S. only, with content that may be different from the U.S. Edition. This may not be resold, copied,
or distributed without the prior consent of the publisher.
, Chapter 1
Introduction
Learning Objectives
1. Develop a general understanding of the management science/operations research approach to decision
making.
2. Realize that quantitative applications begin with a problem situation.
3. Obtain a brief introduction to quantitative techniques and their frequency of use in practice.
4. Understand that managerial problem situations have both quantitative and qualitative considerations
that are important in the decision making process.
5. Learn about models in terms of what they are and why they are useful (the emphasis is on
mathematical models).
6. Identify the step-by-step procedure that is used in most quantitative approaches to decision making.
7. Learn about basic models of cost, revenue, and profit and be able to compute the break-even point.
8. Obtain an introduction to microcomputer software packages and their role in quantitative approaches
to decision making.
9. Understand the following terms:
model infeasible solution
objective function management science
constraint operations research
deterministic model fixed cost
stochastic model variable cost
feasible solution break-even point
Solutions:
1-1
This edition is intended for use outside of the U.S. only, with content that may be different from the U.S. Edition. This may not be resold, copied,
or distributed without the prior consent of the publisher.
An Introduction To
Management Science
Quantitative Approaches
To Decision Making
Twelfth Edition
David R. Anderson
University of Cincinnati
Dennis J. Sweeney
University of Cincinnati
Thomas A. Williams
Rochester Institute of Technology
South-Western
Cincinnati, Ohio
This edition is intended for use outside of the U.S. only, with content that may be different from the U.S. Edition. This may not be resold, copied,
or distributed without the prior consent of the publisher.
, Contents
Preface
Chapter
1. Introduction
2. An Introduction to Linear Programming
3. Linear Programming: Sensitivity Analysis and Interpretation of Solution
4. Linear Programming Applications
5. Linear Programming: The Simplex Method
6. Simplex-Based Sensitivity Analysis and Duality
7. Transportation, Assignment and Transshipment Problems
8. Integer Linear Programming
9. Network Models
10. Project Scheduling: PERT/CPM
11. Inventory Models
12. Waiting Line Models
13. Simulation
14. Decision Analysis
15. Multicriteria Decision Problems
16. Forecasting
17. Markov Processes
18. Dynamic Programming
This edition is intended for use outside of the U.S. only, with content that may be different from the U.S. Edition. This may not be resold, copied,
or distributed without the prior consent of the publisher.
, Preface
The purpose of An Introduction to Management Science is to provide students with a sound
conceptual understanding of the role management science pays in the decision-making
process. The text emphasizes the application of management science by using problem
situations to introduce each of the management science concepts and techniques. The book
has been specifically designed to meet the needs of nonmathematicians who are studying
business and economics.
The Solutions Manual furnishes assistance by identifying learning objectives and providing
detailed solutions for all exercises in the text.
Note: The solutions to the case problems are included in the Solutions to Case Problems
Manual.
Acknowledgements
We would like to provide a special acknowledgement to Catherine J. Williams for her
efforts in preparing the pages for the Solutions Manual. We are also indebted to our
acquisitions editor Charles E. McCormick, Jr. and our developmental editor Alice C. Denny
for their support during the preparation of this manual.
David R. Anderson
Dennis J. Sweeney
Thomas A. Williams
This edition is intended for use outside of the U.S. only, with content that may be different from the U.S. Edition. This may not be resold, copied,
or distributed without the prior consent of the publisher.
, Chapter 1
Introduction
Learning Objectives
1. Develop a general understanding of the management science/operations research approach to decision
making.
2. Realize that quantitative applications begin with a problem situation.
3. Obtain a brief introduction to quantitative techniques and their frequency of use in practice.
4. Understand that managerial problem situations have both quantitative and qualitative considerations
that are important in the decision making process.
5. Learn about models in terms of what they are and why they are useful (the emphasis is on
mathematical models).
6. Identify the step-by-step procedure that is used in most quantitative approaches to decision making.
7. Learn about basic models of cost, revenue, and profit and be able to compute the break-even point.
8. Obtain an introduction to microcomputer software packages and their role in quantitative approaches
to decision making.
9. Understand the following terms:
model infeasible solution
objective function management science
constraint operations research
deterministic model fixed cost
stochastic model variable cost
feasible solution break-even point
Solutions:
1-1
This edition is intended for use outside of the U.S. only, with content that may be different from the U.S. Edition. This may not be resold, copied,
or distributed without the prior consent of the publisher.
