An Introduction to Management Science: Quantitative Approaches
to Decision Making14e
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Australia ● Brazil ● Mexico ● Singapore ● United Kingdom ● United States
David R. Anderson University of Cincinnati
Dennis J. Sweeney University of Cincinnati
Thomas A. Williams Rochester Institute of Technology
Jeffrey D. Camm University of Cincinnati
James J. Cochran
University of Alabama
Michael J. Fry University of Cincinnati
Jeffrey W. Ohlmann
University of Iowa
14e
An Introduction to Management Science: Quantitative Approaches
to Decision Making
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An Introduction to Management Science: Quantitative Approaches to Decision Making, Fourteenth Edition David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann
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Printed in the United States of America Print Number: 01 Print Year: 2014
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Dedication
To My Parents Ray and Ilene Anderson
DRA
To My Parents James and Gladys Sweeney
DJS
To My Parents Phil and Ann Williams
TAW
To My Parents Randall and Jeannine Camm
JDC
To My Wife Teresa
JJC
To My Parents Mike and Cynthia Fry
MJF
To My Parents Willis and Phyllis Ohlmann
JWO
Copyright 2016 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
Copyright 2016 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
Brief Contents
Preface xxi About the Authors xxv Chapter 1 Introduction 1 Chapter 2 An Introduction to Linear Programming 30 Chapter 3 Linear Programming: Sensitivity Analysis
and Interpretation of Solution 94 Chapter 4 Linear Programming Applications in Marketing,
Finance, and Operations Management 154 Chapter 5 Advanced Linear Programming Applications 216 Chapter 6 Distribution and Network Models 258 Chapter 7 Integer Linear Programming 320 Chapter 8 Nonlinear Optimization Models 369 Chapter 9 Project Scheduling: PERT/CPM 418 Chapter 10 Inventory Models 457 Chapter 11 Waiting Line Models 506 Chapter 12 Simulation 547 Chapter 13 Decision Analysis 610 Chapter 14 Multicriteria Decisions 689 Chapter 15 Time Series Analysis and Forecasting 733 Chapter 16 Markov Processes On Website Chapter 17 Linear Programming: Simplex Method On Website Chapter 18 Simplex-Based Sensitivity Analysis and Duality
On Website Chapter 19 Solution Procedures for Transportation and
Assignment Problems On Website Chapter 20 Minimal Spanning Tree On Website Chapter 21 Dynamic Programming On Website Appendixes 787 Appendix A Building Spreadsheet Models 788 Appendix B Areas for the Standard Normal Distribution 815 Appendix C Values of e2! 817 Appendix D References and Bibliography 819 Appendix E Self-Test Solutions and Answers
to Even-Numbered Problems 821 Index 863
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Copyright 2016 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.
Preface xxi About the Authors xxv
Chapter 1 Introduction 1 1.1 Problem Solving and Decision Making 3 1.2 Quantitative Analysis and Decision Making 5 1.3 Quantitative Analysis 7
Model Development 7 Data Preparation 10 Model Solution 11 Report Generation 12 A Note Regarding Implementation 13
1.4 Models of Cost, Revenue, and Profit 14 Cost and Volume Models 14 Revenue and Volume Models 15 Profit and Volume Models 15 Breakeven Analysis 15
1.5 Management Science Techniques 17 Methods Used Most Frequently 18
Summary 19 Glossary 19 Problems 20 Case Problem Scheduling a Golf League 25 Appendix 1.1 Using Excel for Breakeven Analysis 26
Chapter 2 An Introduction to Linear Programming 30 2.1 A Simple Maximization Problem 32
Problem Formulation 33 Mathematical Statement of the Par, Inc., Problem 35
2.2 Graphical Solution Procedure 37 A Note on Graphing Lines 46 Summary of the Graphical Solution Procedure
for Maximization Problems 48 Slack Variables 49
2.3 Extreme Points and the Optimal Solution 50 2.4 Computer Solution of the Par, Inc., Problem 52
Interpretation of Computer Output 53
Contents
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x Contents
2.5 A Simple Minimization Problem 54 Summary of the Graphical Solution Procedure
for Minimization Problems 56 Surplus Variables 57 Computer Solution of the M&D Chemicals Problem 58
2.6 Special Cases 59 Alternative Optimal Solutions 59 Infeasibility 60 Unbounded 62
2.7 General Linear Programming Notation 64 Summary 66 Glossary 67 Problems 68 Case Problem 1 Workload Balancing 84 Case Problem 2 Production Strategy 85 Case Problem 3 Hart Venture Capital 86 Appendix 2.1 Solving Linear Programs with LINGO 87 Appendix 2.2 Solving Linear Programs with Excel Solver 89
Chapter 3 Linear Programming: Sensitivity Analysis and Interpretation of Solution 94
3.1 Introduction to Sensitivity Analysis 96 3.2 Graphical Sensitivity Analysis 97
Objective Function Coefficients 97 Right-Hand Sides 102
3.3 Sensitivity Analysis: Computer Solution 105 Interpretation of Computer Output 105 Cautionary Note on the Interpretation of Dual Values 108 The Modified Par, Inc., Problem 108
3.4 Limitations of Classical Sensitivity Analysis 112 Simultaneous Changes 113 Changes in Constraint Coefficients 114 Nonintuitive Dual Values 114
3.5 The Electronic Communications Problem 118 Problem Formulation 119 Computer Solution and Interpretation 120
Summary 123 Glossary 124 Problems 125 Case Problem 1 Product Mix 146 Case Problem 2 Investment Strategy 147 Case Problem 3 TRUCK LEASING STRATEGY 148 Appendix 3.1 Sensitivity Analysis with Excel Solver 149 Appendix 3.2 Sensitivity Analysis with LINGO 151
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Contents xi
Chapter 4 Linear Programming Applications in Marketing, Finance, and Operations Management 154
4.1 Marketing Applications 155 Media Selection 156 Marketing Research 159
4.2 Financial Applications 162 Portfolio Selection 162 Financial Planning 165
4.3 Operations Management Applications 169 A Make-or-Buy Decision 169 Production Scheduling 173 Workforce Assignment 180 Blending Problems 184
Summary 189 Problems 190 Case Problem 1 Planning An Advertising Campaign 204 Case Problem 2 Schneider’s Sweet Shop 205 Case Problem 3 Textile Mill Scheduling 206 Case Problem 4 Workforce Scheduling 208 Case Problem 5 Duke Energy Coal Allocation 209 Appendix 4.1 Excel Solution of Hewlitt Corporation
Financial Planning Problem 212
Chapter 5 Advanced Linear Programming Applications 216 5.1 Data Envelopment Analysis 217
Evaluating the Performance of Hospitals 218 Overview of the DEA Approach 218 DEA Linear Programming Model 219 Summary of the DEA Approach 224
5.2 Revenue Management 225 5.3 Portfolio Models and Asset Allocation 231
A Portfolio of Mutual Funds 231 Conservative Portfolio 232 Moderate Risk Portfolio 234
5.4 Game Theory 238 Competing for Market Share 238 Identifying a Pure Strategy Solution 241 Identifying a Mixed Strategy Solution 242
Summary 250 Glossary 250 Problems 250
Copyright 2016 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.