AE An Introduction to Management Science: Quantitative Approach,
15th Edition

1. Introduction.
2. An Introduction to Linear Programming.
3. Linear Programming: Sensitivity Analysis and Interpretation of Solution.
4. Linear Programming Applications in Marketing, Finance, and Operations Management.
5. Advanced Linear Programming Applications.
6. Distribution and Network Models.
7. Integer Linear Programming.
8. Nonlinear Optimization Models.
9. Project Scheduling: PERT/CPM.
10. Inventory Models.
11. Waiting Line Models.
12. Simulation.
13. Decision Analysis.
14. Multicriteria Decisions.
15. Time Series Analysis and Forecasting.
16. Markov Processes.
17. Linear Programming: Simplex Method (online).
18. Simplex-Based Sensitivity Analysis and Duality (online).
19. Solutions Procedures for Transportation and Assignment Problems (online).
20. Minimal Spanning Tree (online).
21. Dynamic Programming (online).
Appendix A: Building Spreadsheet Models.
Appendix B: Areas for the Standard Normal Distribution.
Appendix C: Values of e–λ.
Appendix D: References and Bibliography.
Appendix E: Self-Test Solutions and Answers to Even-Numbered Problems (online only).

• David R. Anderson

  David R. Anderson is a leading author and professor emeritus of quantitative analysis in the College of Business Administration at the University of Cincinnati. Dr. Anderson has served as head of the Department of Quantitative Analysis and Operations Management and as associate dean of the College of Business Administration. He was also coordinator of the college’s first executive program. In addition to introductory statistics for business students, Dr. Anderson taught graduate-level courses in regression analysis, multivariate analysis and management science. He also taught statistical courses at the Department of Labor in Washington, D.C. Dr. Anderson has received numerous honors for excellence in teaching and service to student organizations. He is the co-author of ten well-respected textbooks related to decision sciences, and he actively consults with businesses in the areas of sampling and statistical methods. Born in Grand Forks, North Dakota, Dr. Anderson earned his B.S., M.S. and Ph.D. degrees from Purdue University.

• Dennis J. Sweeney

  Dennis J. Sweeney is professor emeritus of quantitative analysis and founder of the Center for Productivity Improvement at the University of Cincinnati. Born in Des Moines, Iowa, he earned a B.S.B.A. degree from Drake University and his M.B.A. and D.B.A. degrees from Indiana University, where he was an NDEA fellow. Dr. Sweeney has worked in the management science group at Procter & Gamble and has been a visiting professor at Duke University. He also served as head of the Department of Quantitative Analysis and served four years as associate dean of the College of Business Administration at the University of Cincinnati. Dr. Sweeney has published more than 30 articles and monographs in the area of management science and statistics. The National Science Foundation, IBM, Procter & Gamble, Federated Department Stores, Kroger and Cincinnati Gas & Electric have funded his research, which has been published in journals such as Management Science, Operations Research, Mathematical Programming and Decision Sciences. Dr. Sweeney has co-authored ten textbooks in the areas of statistics, management science, linear programming and production and operations management.

• Thomas A. Williams

  N/A

• Jeffrey D. Camm

  Jeffrey D. Camm is the Inmar Presidential Chair of Analytics and Senior Associate Dean of Business Analytics programs in the School of Business at Wake Forest University. Born in Cincinnati, Ohio, he holds a B.S. from Xavier University (Ohio) and a Ph.D. from Clemson University. Prior to joining the faculty at Wake Forest, Dr. Camm served on the faculty of the University of Cincinnati. He has also been a visiting scholar at Stanford University and a visiting professor of business administration at the Tuck School of Business at Dartmouth College. Dr. Camm has published more than 45 papers in the general area of optimization applied to problems in operations management and marketing. He has published his research in Science, Management Science, Operations Research, Interfaces and other professional journals. Dr. Camm was named the Dornoff Fellow of Teaching Excellence at the University of Cincinnati and he was the recipient of the 2006 INFORMS Prize for the Teaching of Operations Research Practice. A firm believer in practicing what he preaches, he has served as an operations research consultant to numerous companies and government agencies. From 2005 to 2010, Dr. Camm served as editor-in-chief of INFORMS Journal of Applied Analytics (formerly Interfaces). In 2017, he was named an INFORMS fellow.

• James J. Cochran

  James J. Cochran is Professor of Applied Statistics, the Rogers-Spivey Faculty Fellow and Associate Dean for Faculty and Research at the University of Alabama. Born in Dayton, Ohio, he earned his B.S., M.S., and M.B.A. degrees from Wright State University and his Ph.D. from the University of Cincinnati. Dr. Cochran has served at The University of Alabama since 2014 and has been a visiting scholar at Stanford University, Universidad de Talca, the University of South Africa and Pole Universitaire Leonard de Vinci. Dr. Cochran has published more than 45 papers in the development and application of operations research and statistical methods. He has published his research in Management Science, The American Statistician, Communications in Statistics-Theory and Methods, Annals of Operations Research, European Journal of Operational Research, Journal of Combinatorial Optimization, INFORMS Journal of Applied Analytics and Statistics and Probability Letters. He was the 2008 recipient of the INFORMS Prize for the Teaching of Operations Research Practice and the 2010 recipient of the Mu Sigma Rho Statistical Education Award. Dr. Cochran was elected to the International Statistics Institute in 2005 and named a fellow of the American Statistical Association in 2011. He received the Founders Award in 2014 and the Karl E. Peace Award in 2015 from the American Statistical Association. In 2017 he received the American Statistical Association’s Waller Distinguished Teaching Career Award and was named a fellow of INFORMS. In 2018 he received the INFORMS President’s Award. A strong advocate for effective statistics and operations research education as a means of improving the quality of applications to real problems, Dr. Cochran has organized and chaired teaching workshops throughout the world.

• Michael J. Fry

  Michael J. Fry is Professor of Operations, Business Analytics and Information Systems and Academic Director of the Center for Business Analytics in the Carl H. Lindner College of Business at the University of Cincinnati. Born in Killeen, Texas, he earned a B.S. from Texas A&M University and his M.S.E. and Ph.D. from the University of Michigan. He has been at the University of Cincinnati since 2002, where he was previously department head. Dr. Fry has been named a Lindner Research Fellow. He has also been a visiting professor at the Samuel Curtis Johnson Graduate School of Management at Cornell University and the Sauder School of Business at the University of British Columbia. Dr. Fry has published more than 25 research papers in journals such as Operations Research, M&SOM, Transportation Science, Naval Research Logistics, IISE Transactions, Critical Care Medicine and INFORMS Journal of Applied Analytics (formerly Interfaces). His research interests are in applying quantitative management methods to the areas of supply chain analytics, sports analytics and public-policy operations. He has worked with many organizations for his research, including Dell, Inc., Starbucks Coffee Company, Great American Insurance Group, the Cincinnati Fire Department, the State of Ohio Election Commission, the Cincinnati Bengals and the Cincinnati Zoo and Botanical Garden. Dr. Fry was named a finalist for the Daniel H. Wagner Prize for Excellence in Operations Research Practice, and he has been recognized for both his research and teaching excellence at the University of Cincinnati.

• Jeffrey W. Ohlmann

  Jeffrey W. Ohlmann is Associate Professor of Management Sciences and Huneke Research Fellow in the Tippie College of Business at the University of Iowa. Born in Valentine, Nebraska, he earned a B.S. from the University of Nebraska, and his M.S. and Ph.D. from the University of Michigan. He has been at the University of Iowa since 2003. Dr. Ohlmann’s research on the modeling and solution of decision-making problems has produced more than two dozen research papers in journals such as Operations Research, Mathematics of Operations Research, INFORMS Journal on Computing, Transportation Science, the European Journal of Operational Research and INFORMS Journal of Applied Analytics (formerly Interfaces). He has collaborated with companies such as Transfreight, LeanCor, Cargill, the Hamilton County Board of Elections as well as three National Football League franchises. Because of the relevance of his work to industry, he was bestowed the George B. Dantzig Dissertation Award and was recognized as a finalist for the Daniel H. Wagner Prize for Excellence in Operations Research Practice.

• PROVEN AUTHOR TEAM DELIVERS LEADING, TRUSTED PRESENTATION. Respected leaders and active consultants in the fields of business and statistics, the Anderson/Sweeney/Williams/Camm/Cochran/Fry/Ohlmann team of authors personally write and confirm all of this edition's explanations, examples, problems, as well as Test Bank content to ensure unwavering accuracy and dependability.

• PROBLEM-SCENARIO APPROACH ENSURES COMPREHENSION. A hallmark strength of this text, the authors' proven problem-scenario approach introduces problems using the management science model and introduces each quantitative technique within an application setting. Students must apply the management science technique to each problem to generate a business solution or recommendation.

• SELF-TEST EXERCISES ENSURE UNDERSTANDING. Helpful Self-Test Exercises throughout each chapter with complete solutions allow students to check their understanding of concepts as they progress through the text. The exercises also serve as excellent exam-prep tools. A complete, step-by-step solution to each Self-Test exercise is included in the online Appendix E.

• REAL DATA EXAMPLES DEMONSTRATE ACTUAL BUSINESS SITUATIONS AND CHALLENGES. Known for its practical, real-world emphasis, this book provides actual data drawn from real business that emphasizes applications as well as solid management science and quantitative methodology.

• INTEGRATED SOFTWARE APPLICATIONS HELP STUDENTS MASTER CRITICAL SKILLS. The text integrates coverage of the software applications most commonly used today, helping you equip students with critical skills in LINGO as well as Excel with quantitative add-ins. For your convenience, coverage of LINGO and Excel with add-in Analytic Solver Platform appears in the appendixes. This allows you to introduce this content when it best fits within your course.

• ROBUST ONLINE CONTENT REINFORCES AND EXPANDS UPON THE BOOK'S EXPLANATIONS. This edition's wealth of digital content provides five online chapters, Excel templates and add-ins that correspond with text examples and models and software. Students can also access LINGO trial edition software and Analytic Solver Platform.

• PROVEN AUTHOR TEAM DELIVERS LEADING, TRUSTED PRESENTATION. Respected leaders and active consultants in the fields of business and statistics, the Anderson/Sweeney/Williams/Camm/Cochran/Fry/Ohlmann team of authors personally write and confirm all of this edition's explanations, examples, problems, as well as Test Bank content to ensure unwavering accuracy and dependability.

• PROBLEM-SCENARIO APPROACH ENSURES COMPREHENSION. A hallmark strength of this text, the authors' proven problem-scenario approach introduces problems using the management science model and introduces each quantitative technique within an application setting. Students must apply the management science technique to each problem to generate a business solution or recommendation.

• SELF-TEST EXERCISES ENSURE UNDERSTANDING. Helpful Self-Test Exercises throughout each chapter with complete solutions allow students to check their understanding of concepts as they progress through the text. The exercises also serve as excellent exam-prep tools. A complete, step-by-step solution to each Self-Test exercise is included in the online Appendix E.

• REAL DATA EXAMPLES DEMONSTRATE ACTUAL BUSINESS SITUATIONS AND CHALLENGES. Known for its practical, real-world emphasis, this book provides actual data drawn from real business that emphasizes applications as well as solid management science and quantitative methodology.

• INTEGRATED SOFTWARE APPLICATIONS HELP STUDENTS MASTER CRITICAL SKILLS. The text integrates coverage of the software applications most commonly used today, helping you equip students with critical skills in LINGO as well as Excel with quantitative add-ins. For your convenience, coverage of LINGO and Excel with add-in Analytic Solver Platform appears in the appendixes. This allows you to introduce this content when it best fits within your course.

• ROBUST ONLINE CONTENT REINFORCES AND EXPANDS UPON THE BOOK'S EXPLANATIONS. This edition's wealth of digital content provides five online chapters, Excel templates and add-ins that correspond with text examples and models and software. Students can also access LINGO trial edition software and Analytic Solver Platform.

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