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Tenth Edition
Bernard W. Taylor III
Virginia Polytechnic Institute and State University
Prentice Hall
Upper Saddle River, New Jersey 07458
Introduction to
Management Science
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Introduction to Management Science, Tenth Edition, by Bernard
W. Taylor III. Published by Prentice Hall. Copyright © 2010 by
Pearson Education, Inc.
Library of Congress Cataloging-in-Publication Data
Taylor, Bernard W.
Introduction to management science / Bernard W. Taylor III.—
10th ed.
p. cm.
Includes bibliographical references and index.
ISBN-13: 978-0-13-606436-7 (alk. paper)
ISBN-10: 0-13-606436-1 (alk. paper)
1. Management science. I. Title.
T56.T38 2009
658.5—dc21
2008053963
Executive Editor: Mark Pfaltzgraff
Editor In Chief: Eric Svendsen
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Morris
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Bartunek
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Credits and acknowledgments borrowed from other sources and
reproduced, with permission,
in this textbook appear on appropriate page within text or on
page 815.
Microsoft® and Windows® are registered trademarks of the
Microsoft Corporation in the
U.S.A. and other countries. Screen shots and icons reprinted
with permission from the
Microsoft Corporation. This book is not sponsored or endorsed
by or affiliated with the
Microsoft Corporation.
Copyright © 2010, 2007, 2004, 2002, 1999, 1996 by Pearson
Education, Inc., Upper Saddle
River, New Jersey, 07458. Pearson Prentice Hall. All rights
reserved. Printed in the United
States of America. This publication is protected by Copyright
and permission should be
obtained from the publisher prior to any prohibited
reproduction, storage in a retrieval
system, or transmission in any form or by any means,
electronic, mechanical, photocopying,
recording, or likewise. For information regarding permission(s),
write to: Rights and
Permissions Department.
Pearson Prentice Hall™ is a trademark of Pearson Education,
Inc.
Pearson® is a registered trademark of Pearson plc
Prentice Hall® is a registered trademark of Pearson Education,
Inc.
Pearson Education Ltd., London Pearson Education North Asia,
Ltd., Hong Kong
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Mexico, S.A. de C.V.
Pearson Education, Canada, Inc. Pearson Education Malaysia,
Pte. Ltd
Pearson Education–Japan Pearson Education Upper Saddle
River, New Jersey
Pearson Education Australia PTY, Limited
10 9 8 7 6 5 4 3 2 1
ISBN-13: 978-0-13-606436-7
ISBN-10: 0-13-606436-1
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Introduction to Management Science, Tenth Edition, by Bernard
W. Taylor III. Published by Prentice Hall. Copyright © 2010 by
Pearson Education, Inc.
1
C h a p t e r 1
Management Science
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Introduction to Management Science, Tenth Edition, by Bernard
W. Taylor III. Published by Prentice Hall. Copyright © 2010 by
Pearson Education, Inc.
2 Chapter 1 Management Science
Management science is a
scientific approach to solving
management problems.
Management science is the application of a scientific approach
to solving managementproblems in order to help managers make
better decisions. As implied by this defini-
tion, management science encompasses a number of
mathematically oriented techniques
that have either been developed within the field of management
science or been adapted
from other disciplines, such as the natural sciences,
mathematics, statistics, and engineer-
ing. This text provides an introduction to the techniques that
make up management
science and demonstrates their applications to management
problems.
Management science is a recognized and established discipline
in business. The applica-
tions of management science techniques are widespread, and
they have been frequently
credited with increasing the efficiency and productivity of
business firms. In various sur-
veys of businesses, many indicate that they use management
science techniques, and most
rate the results to be very good. Management science (also
referred to as operations research,
quantitative methods, quantitative analysis, and decision
sciences) is part of the fundamental
curriculum of most programs in business.
As you proceed through the various management science models
and techniques con-
tained in this text, you should remember several things. First,
most of the examples pre-
sented in this text are for business organizations because
businesses represent the main
users of management science. However, management science
techniques can be applied to
solve problems in different types of organizations, including
services, government, mili-
tary, business and industry, and health care.
Second, in this text all of the modeling techniques and solution
methods are mathemat-
ically based. In some instances the manual, mathematical
solution approach is shown
because it helps one understand how the modeling techniques
are applied to different
problems. However, a computer solution is possible for each of
the modeling techniques in
this text, and in many cases the computer solution is
emphasized. The more detailed math-
ematical solution procedures for many of the modeling
techniques are included as supple-
mental modules on the companion Web site for this text.
Finally, as the various management science techniques are
presented, keep in mind that
management science is more than just a collection of
techniques. Management science also
involves the philosophy of approaching a problem in a logical
manner (i.e., a scientific
approach). The logical, consistent, and systematic approach to
problem solving can be as
useful (and valuable) as the knowledge of the mechanics of the
mathematical techniques
themselves. This understanding is especially important for those
readers who do not always
see the immediate benefit of studying mathematically oriented
disciplines such as manage-
ment science.
The Management Science Approach to Problem Solving
As indicated in the previous section, management science
encompasses a logical, systematic
approach to problem solving, which closely parallels what is
known as the scientific
method for attacking problems. This approach, as shown in
Figure 1.1, follows a generally
recognized and ordered series of steps: (1) observation, (2)
definition of the problem,
(3) model construction, (4) model solution, and (5)
implementation of solution results.
We will analyze each of these steps individually.
Observation
The first step in the management science process is the
identification of a problem that
exists in the system (organization). The system must be
continuously and closely observed
Management science can be used
in a variety of organizations to
solve many different types of
problems.
Management science encompasses
a logical approach to problem
solving.
The steps of the scientific method
are (1) observation, (2) problem
definition, (3) model construction,
(4) model solution, and
(5) implementation.
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Introduction to Management Science, Tenth Edition, by Bernard
W. Taylor III. Published by Prentice Hall. Copyright © 2010 by
Pearson Education, Inc.
so that problems can be identified as soon as they occur or are
anticipated. Problems are
not always the result of a crisis that must be reacted to but,
instead, frequently involve an
anticipatory or planning situation. The person who normally
identifies a problem is the
manager because managers work in places where problems
might occur. However, prob-
lems can often be identified by a management scientist, a person
skilled in the techniques
of management science and trained to identify problems, who
has been hired specifically to
solve problems using management science techniques.
Definition of the Problem
Once it has been determined that a problem exists, the problem
must be clearly and con-
cisely defined. Improperly defining a problem can easily result
in no solution or an inap-
propriate solution. Therefore, the limits of the problem and the
degree to which it pervades
other units of the organization must be included in the problem
definition. Because the
existence of a problem implies that the objectives of the firm
are not being met in some
way, the goals (or objectives) of the organization must also be
clearly defined. A stated
objective helps to focus attention on what the problem actually
is.
Model Construction
A management science model is an abstract representation of an
existing problem situa-
tion. It can be in the form of a graph or chart, but most
frequently a management science
model consists of a set of mathematical relationships. These
mathematical relationships are
made up of numbers and symbols.
As an example, consider a business firm that sells a product.
The product costs $5 to
produce and sells for $20. A model that computes the total
profit that will accrue from the
items sold is
In this equation x represents the number of units of the product
that are sold, and Z rep-
resents the total profit that results from the sale of the product.
The symbols x and Z are
variables. The term variable is used because no set numeric
value has been specified for these
items. The number of units sold, x, and the profit, Z, can be any
amount (within limits); they
can vary. These two variables can be further distinguished. Z is
a dependent variable because
Z = $20x - 5x
The Management Science Approach to Problem Solving 3
Management
science
techniques
Observation
Problem
definition
Model
construction
Solution
Feedback
Information
Implementation
Figure 1.1
The management science
process
A management scientist is a
person skilled in the application of
management science techniques.
A variable is a symbol used to
represent an item that can take on
any value.
A model is an abstract
mathematical representation of a
problem situation.
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Introduction to Management Science, Tenth Edition, by Bernard
W. Taylor III. Published by Prentice Hall. Copyright © 2010 by
Pearson Education, Inc.
4 Chapter 1 Management Science
its value is dependent on the number of units sold; x is an
independent variable because the
number of units sold is not dependent on anything else (in this
equation).
The numbers $20 and $5 in the equation are referred to as
parameters. Parameters are
constant values that are generally coefficients of the variables
(symbols) in an equation.
Parameters usually remain constant during the process of
solving a specific problem. The
parameter values are derived from data (i.e., pieces of
information) from the problem envi-
ronment. Sometimes the data are readily available and quite
accurate. For example, pre-
sumably the selling price of $20 and product cost of $5 could be
obtained from the firm’s
accounting department and would be very accurate. However,
sometimes data are not as
readily available to the manager or firm, and the parameters
must be either estimated or
based on a combination of the available data and estimates. In
such cases, the model is only
as accurate as the data used in constructing the model.
The equation as a whole is known as a functional relationship
(also called function and
relationship). The term is derived from the fact that profit, Z, is
a function of the number of
units sold, x, and the equation relates profit to units sold.
Because only one functional relationship exists in this example,
it is also the model. In
this case the relationship is a model of the determination of
profit for the firm. However,
this model does not really replicate a problem. Therefore, we
will expand our example to
create a problem situation.
Let us assume that the product is made from steel and that the
business firm has 100
pounds of steel available. If it takes 4 pounds of steel to make
each unit of the product, we
can develop an additional mathematical relationship to represent
steel usage:
This equation indicates that for every unit produced, 4 of the
available 100 pounds of
steel will be used. Now our model consists of two relationships:
We say that the profit equation in this new model is an
objective function, and the
resource equation is a constraint. In other words, the objective
of the firm is to achieve as
much profit, Z, as possible, but the firm is constrained from
achieving an infinite profit by
the limited amount of steel available. To signify this distinction
between the two relation-
ships in this model, we will add the following notations:
subject to
This model now represents the manager’s problem of
determining the number of units
to produce. You will recall that we defined the number of units
to be produced as x. Thus,
when we determine the value of x, it represents a potential (or
recommended) decision for
the manager. Therefore, x is also known as a decision variable.
The next step in the manage-
ment science process is to solve the model to determine the
value of the decision variable.
Model

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Tenth EditionBernard W. Taylor IIIVirginia Polytechnic I.docx

  • 1. Tenth Edition Bernard W. Taylor III Virginia Polytechnic Institute and State University Prentice Hall Upper Saddle River, New Jersey 07458 Introduction to Management Science IS B N 0 -5 5 8 -5 5 5 1 9 -5 Introduction to Management Science, Tenth Edition, by Bernard
  • 2. W. Taylor III. Published by Prentice Hall. Copyright © 2010 by Pearson Education, Inc. Library of Congress Cataloging-in-Publication Data Taylor, Bernard W. Introduction to management science / Bernard W. Taylor III.— 10th ed. p. cm. Includes bibliographical references and index. ISBN-13: 978-0-13-606436-7 (alk. paper) ISBN-10: 0-13-606436-1 (alk. paper) 1. Management science. I. Title. T56.T38 2009 658.5—dc21 2008053963 Executive Editor: Mark Pfaltzgraff Editor In Chief: Eric Svendsen Editorial Project Manager: Susie Abraham Editorial Assistant: Valerie Patruno Senior Marketing Manager: Anne Fahlgren Marketing Assistant: Susan Osterlitz Permissions Project Manager: Charles Morris Senior Managing Editor: Judy Leale Production Project Manager: Clara Bartunek Senior Operations Specialist: Arnold Vila
  • 3. Operations Specialist: Ben Smith Cover Art Director: Jayne Conte Cover Designer: Jayne Conte Cover Illustration/Photo: Shutterstock, Inc. Interior Art Director: Anthony Gemmellaro Interior Designer: Maria Guglielmo Manager, Rights and Permissions: Zina Arabia Manager, Visual Research: Beth Brenzel Image Permission Coordinator: Jan Marc Quisumbing Photo Researcher: Jane Scelta Manager, Cover Visual Research & Permissions: Karen Sanatar Composition: GGS Higher Education Resources, a Divison of Premedia Global, Inc. Full-Service Project Management: Heidi Allgair/GGS Higher Education Resources, a Divison of PreMedia Global, Inc. Interior Printer/Binder: Edwards Brothers Cover Printer: Lehigh - Phoenix Color Corp./Hagerstown Typeface: 10/12 Minion Credits and acknowledgments borrowed from other sources and reproduced, with permission, in this textbook appear on appropriate page within text or on
  • 4. page 815. Microsoft® and Windows® are registered trademarks of the Microsoft Corporation in the U.S.A. and other countries. Screen shots and icons reprinted with permission from the Microsoft Corporation. This book is not sponsored or endorsed by or affiliated with the Microsoft Corporation. Copyright © 2010, 2007, 2004, 2002, 1999, 1996 by Pearson Education, Inc., Upper Saddle River, New Jersey, 07458. Pearson Prentice Hall. All rights reserved. Printed in the United States of America. This publication is protected by Copyright and permission should be obtained from the publisher prior to any prohibited reproduction, storage in a retrieval system, or transmission in any form or by any means, electronic, mechanical, photocopying, recording, or likewise. For information regarding permission(s), write to: Rights and Permissions Department. Pearson Prentice Hall™ is a trademark of Pearson Education, Inc. Pearson® is a registered trademark of Pearson plc Prentice Hall® is a registered trademark of Pearson Education, Inc. Pearson Education Ltd., London Pearson Education North Asia, Ltd., Hong Kong Pearson Education Singapore, Pte. Ltd Pearson Educación de Mexico, S.A. de C.V. Pearson Education, Canada, Inc. Pearson Education Malaysia, Pte. Ltd
  • 5. Pearson Education–Japan Pearson Education Upper Saddle River, New Jersey Pearson Education Australia PTY, Limited 10 9 8 7 6 5 4 3 2 1 ISBN-13: 978-0-13-606436-7 ISBN-10: 0-13-606436-1 IS B N 0 -5 5 8 -5 5 5 1 9 -5 Introduction to Management Science, Tenth Edition, by Bernard W. Taylor III. Published by Prentice Hall. Copyright © 2010 by Pearson Education, Inc. 1
  • 6. C h a p t e r 1 Management Science IS B N 0 -5 5 8 -5 5 5 1 9 -5 Introduction to Management Science, Tenth Edition, by Bernard W. Taylor III. Published by Prentice Hall. Copyright © 2010 by Pearson Education, Inc. 2 Chapter 1 Management Science Management science is a scientific approach to solving
  • 7. management problems. Management science is the application of a scientific approach to solving managementproblems in order to help managers make better decisions. As implied by this defini- tion, management science encompasses a number of mathematically oriented techniques that have either been developed within the field of management science or been adapted from other disciplines, such as the natural sciences, mathematics, statistics, and engineer- ing. This text provides an introduction to the techniques that make up management science and demonstrates their applications to management problems. Management science is a recognized and established discipline in business. The applica- tions of management science techniques are widespread, and they have been frequently credited with increasing the efficiency and productivity of business firms. In various sur- veys of businesses, many indicate that they use management science techniques, and most rate the results to be very good. Management science (also referred to as operations research, quantitative methods, quantitative analysis, and decision sciences) is part of the fundamental curriculum of most programs in business. As you proceed through the various management science models and techniques con- tained in this text, you should remember several things. First, most of the examples pre- sented in this text are for business organizations because businesses represent the main
  • 8. users of management science. However, management science techniques can be applied to solve problems in different types of organizations, including services, government, mili- tary, business and industry, and health care. Second, in this text all of the modeling techniques and solution methods are mathemat- ically based. In some instances the manual, mathematical solution approach is shown because it helps one understand how the modeling techniques are applied to different problems. However, a computer solution is possible for each of the modeling techniques in this text, and in many cases the computer solution is emphasized. The more detailed math- ematical solution procedures for many of the modeling techniques are included as supple- mental modules on the companion Web site for this text. Finally, as the various management science techniques are presented, keep in mind that management science is more than just a collection of techniques. Management science also involves the philosophy of approaching a problem in a logical manner (i.e., a scientific approach). The logical, consistent, and systematic approach to problem solving can be as useful (and valuable) as the knowledge of the mechanics of the mathematical techniques themselves. This understanding is especially important for those readers who do not always see the immediate benefit of studying mathematically oriented disciplines such as manage- ment science.
  • 9. The Management Science Approach to Problem Solving As indicated in the previous section, management science encompasses a logical, systematic approach to problem solving, which closely parallels what is known as the scientific method for attacking problems. This approach, as shown in Figure 1.1, follows a generally recognized and ordered series of steps: (1) observation, (2) definition of the problem, (3) model construction, (4) model solution, and (5) implementation of solution results. We will analyze each of these steps individually. Observation The first step in the management science process is the identification of a problem that exists in the system (organization). The system must be continuously and closely observed Management science can be used in a variety of organizations to solve many different types of problems. Management science encompasses a logical approach to problem solving. The steps of the scientific method are (1) observation, (2) problem definition, (3) model construction, (4) model solution, and
  • 10. (5) implementation. IS B N 0 -5 5 8 -5 5 5 1 9 -5 Introduction to Management Science, Tenth Edition, by Bernard W. Taylor III. Published by Prentice Hall. Copyright © 2010 by Pearson Education, Inc. so that problems can be identified as soon as they occur or are anticipated. Problems are not always the result of a crisis that must be reacted to but, instead, frequently involve an anticipatory or planning situation. The person who normally identifies a problem is the manager because managers work in places where problems
  • 11. might occur. However, prob- lems can often be identified by a management scientist, a person skilled in the techniques of management science and trained to identify problems, who has been hired specifically to solve problems using management science techniques. Definition of the Problem Once it has been determined that a problem exists, the problem must be clearly and con- cisely defined. Improperly defining a problem can easily result in no solution or an inap- propriate solution. Therefore, the limits of the problem and the degree to which it pervades other units of the organization must be included in the problem definition. Because the existence of a problem implies that the objectives of the firm are not being met in some way, the goals (or objectives) of the organization must also be clearly defined. A stated objective helps to focus attention on what the problem actually is. Model Construction A management science model is an abstract representation of an existing problem situa- tion. It can be in the form of a graph or chart, but most frequently a management science model consists of a set of mathematical relationships. These mathematical relationships are made up of numbers and symbols. As an example, consider a business firm that sells a product. The product costs $5 to produce and sells for $20. A model that computes the total profit that will accrue from the
  • 12. items sold is In this equation x represents the number of units of the product that are sold, and Z rep- resents the total profit that results from the sale of the product. The symbols x and Z are variables. The term variable is used because no set numeric value has been specified for these items. The number of units sold, x, and the profit, Z, can be any amount (within limits); they can vary. These two variables can be further distinguished. Z is a dependent variable because Z = $20x - 5x The Management Science Approach to Problem Solving 3 Management science techniques Observation Problem definition Model construction Solution
  • 13. Feedback Information Implementation Figure 1.1 The management science process A management scientist is a person skilled in the application of management science techniques. A variable is a symbol used to represent an item that can take on any value. A model is an abstract mathematical representation of a
  • 14. problem situation. IS B N 0 -5 5 8 -5 5 5 1 9 -5 Introduction to Management Science, Tenth Edition, by Bernard W. Taylor III. Published by Prentice Hall. Copyright © 2010 by
  • 15. Pearson Education, Inc. 4 Chapter 1 Management Science its value is dependent on the number of units sold; x is an independent variable because the number of units sold is not dependent on anything else (in this equation). The numbers $20 and $5 in the equation are referred to as parameters. Parameters are constant values that are generally coefficients of the variables (symbols) in an equation. Parameters usually remain constant during the process of solving a specific problem. The parameter values are derived from data (i.e., pieces of information) from the problem envi- ronment. Sometimes the data are readily available and quite accurate. For example, pre- sumably the selling price of $20 and product cost of $5 could be obtained from the firm’s accounting department and would be very accurate. However, sometimes data are not as
  • 16. readily available to the manager or firm, and the parameters must be either estimated or based on a combination of the available data and estimates. In such cases, the model is only as accurate as the data used in constructing the model. The equation as a whole is known as a functional relationship (also called function and relationship). The term is derived from the fact that profit, Z, is a function of the number of units sold, x, and the equation relates profit to units sold. Because only one functional relationship exists in this example, it is also the model. In this case the relationship is a model of the determination of profit for the firm. However, this model does not really replicate a problem. Therefore, we will expand our example to create a problem situation. Let us assume that the product is made from steel and that the business firm has 100 pounds of steel available. If it takes 4 pounds of steel to make each unit of the product, we can develop an additional mathematical relationship to represent
  • 17. steel usage: This equation indicates that for every unit produced, 4 of the available 100 pounds of steel will be used. Now our model consists of two relationships: We say that the profit equation in this new model is an objective function, and the resource equation is a constraint. In other words, the objective of the firm is to achieve as much profit, Z, as possible, but the firm is constrained from achieving an infinite profit by the limited amount of steel available. To signify this distinction between the two relation- ships in this model, we will add the following notations: subject to This model now represents the manager’s problem of determining the number of units to produce. You will recall that we defined the number of units to be produced as x. Thus, when we determine the value of x, it represents a potential (or recommended) decision for the manager. Therefore, x is also known as a decision variable.
  • 18. The next step in the manage- ment science process is to solve the model to determine the value of the decision variable. Model