Need Help In Management Science

University of the Incarnate Word

BMGT 3371

Course: Management Science

Chapter 9 Homework

· Problem 6 – Page 445 in Anderson et al., Text

· Problem 7 – Page 445 in Anderson et al., Text

· Problem 9 – Page 446 in Anderson et al., Text

· Problem 14 – Page 448 in Anderson et al., Text

· Problem 15 – Page 449 in Anderson et al., Text

· Problem 18 – Page 450 in Anderson et al., Text

· Problem 19 – Page 450 in Anderson et al., Text

· Problem 21 – Page 452 in Anderson et al., Text

· Problem 22 – Page 453 in Anderson et al., Text

· Problem 24 – Page 453 in Anderson et al., Text

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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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

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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 e2l 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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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

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xii Contents

Chapter 6 Distribution and Network Models 258 6.1 Supply Chain Models 259

Transportation Problem 259 Problem Variations 262 A General Linear Programming Model 265 Transshipment Problem 266 Problem Variations 272 A General Linear Programming Model 272

6.2 Assignment Problem 274 Problem Variations 277 A General Linear Programming Model 277

6.3 Shortest-Route Problem 279 A General Linear Programming Model 282

6.4 Maximal Flow Problem 283 6.5 A Production and Inventory Application 287 Summary 290 Glossary 291 Problems 292 Case Problem 1 Solutions Plus 309 Case Problem 2 Supply Chain Design 311 Appendix 6.1 Excel Solution of Transportation, Transshipment,

and Assignment Problems 312

Chapter 7 Integer Linear Programming 320 7.1 Types of Integer Linear Programming Models 322 7.2 Graphical and Computer Solutions for an All-Integer

Linear Program 324 Graphical Solution of the LP Relaxation 325 Rounding to Obtain an Integer Solution 325 Graphical Solution of the All-Integer Problem 326 Using the LP Relaxation to Establish Bounds 326 Computer Solution 327

7.3 Applications Involving 0-1 Variables 328 Capital Budgeting 328 Fixed Cost 329 Distribution System Design 332 Bank Location 337 Product Design and Market Share Optimization 340

7.4 Modeling Flexibility Provided by 0-1 Integer Variables 344 Multiple-Choice and Mutually Exclusive Constraints 344 k out of n Alternatives Constraint 345 Conditional and Corequisite Constraints 345 A Cautionary Note About Sensitivity Analysis 347

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