AE An Introduction to Management Science,
16th 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.
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: Answers to Even-Numbered Problems (online only).

• Jeffrey D. Camm

  Jeffrey D. Camm is the Inmar Presidential Chair 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, he 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 many professional journals, including Science, Management Science, Operations Research and the INFORMS Journal on Applied Analytics. Dr. Camm was named the Dornoff Fellow of Teaching Excellence at the University of Cincinnati, and he was the 2006 recipient of the INFORMS Prize for the Teaching of Operations Research Practice. A firm believer in practicing what he preaches, Dr. Camm has served as an operations research consultant to numerous companies and government agencies. From 2005 to 2010 he served as editor-in-chief of the INFORMS Journal on Applied Analytics (formerly Interfaces). In 2016 Dr. Camm received the George E. Kimball Medal for service to the operations research profession, and in 2017 he was named an INFORMS fellow.

• James J. Cochran

  James J. Cochran is associate dean for research, a professor of applied statistics and the Rogers-Spivey Faculty Fellow at The University of Alabama. Born in Dayton, Ohio, he earned his B.S., M.S. and M.B.A. from Wright State University and his Ph.D. from the University of Cincinnati. He has been at The University of Alabama since 2014 and has served as 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 50 papers in the development and application of operations research and statistical methods. He has published in numerous journals, including 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 on Applied Analytics, BMJ Global Health and Statistics and Probability Letters. Dr. Cochran received the 2008 INFORMS prize for the Teaching of Operations Research Practice, the 2010 Mu Sigma Rho Statistical Education Award and the 2016 Waller Distinguished Teaching Career Award from the American Statistical Association. Dr. Cochran was elected to the International Statistics Institute in 2005 and was named a fellow of the American Statistical Association in 2011 and a fellow of INFORMS in 2017. He also received the Founders Award in 2014 and the Karl E. Peace Award in 2015 from the American Statistical Association. In addition, he received the INFORMS President's Award in 2019. A strong advocate for effective operations research and statistics education as a means of improving the quality of applications to real problems, Dr. Cochran has chaired teaching effectiveness workshops around the globe. He has also served as an operations research or statistics consultant to numerous companies and not-for-profit organizations.

• Michael J. Fry

  Michael J. Fry is a professor of operations, business analytics and information systems as well as 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, Dr. Fry earned his B.S. from Texas A&M University and M.S.E. and Ph.D. degrees from the University of Michigan. He has been at the University of Cincinnati since 2002, where he was previously department head. He has also been named a Lindner Research Fellow. Dr. Fry 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.He has published more than 25 research papers in journals such as Operations Research, M&SOM, Transportation Science, Naval Research Logistics, IIE Transactions, Critical Care Medicine and 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 different 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 & Botanical Garden. He 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 business analytics and a 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 M.S. and Ph.D. degrees from the University of Michigan. Dr. Ohlmann has been at the University of Iowa since 2003. His research on the modeling and solution of decision-making problems has produced more than two dozen research papers published in journals such as Operations Research, Mathematics of Operations Research, INFORMS Journal on Computing, Transportation Science and the European Journal of Operational Research. He has collaborated with organizations such as Transfreight, LeanCor, Cargill, the Hamilton County Board of Elections and three National Football League franchises. Because of the relevance of his work to industry, Dr. Ohlmann received the George B. Dantzig Dissertation Award, and he was recognized as a finalist for the Daniel H. Wagner Prize for Excellence in Operations Research Practice.

• 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

• REVISIONS, GUIDED BY READER FEEDBACK, FURTHER IMPROVE CONCEPT EXPLANATIONS. Expanded discussions clarify key concepts. For instance, Chapter 7 clearly introduces the feasibility table to aid the construction of conditional and corequisite constraints. Chapter 8 expands discussion of sensitivity analysis for nonlinear optimization, and Chapter 10 clarifies the when-to-order decision for the various inventory models. In addition, Chapter 11 offers revised technical notes on multiple-server queueing systems.

• NEW "MANAGEMENT SCIENCE IN ACTION" VIGNETTES AND PROBLEMS DEMONSTRATE CONCEPTS AT WORK. Six new "Management Science in Action" vignettes describe how material covered in this edition is actually used in practice today. In addition, more than 15 end-of-chapter problems are new and many are updated.

• FULL-COLOR INTERNAL DESIGN APPEALS TO STUDENTS AND HELPS CLARIFY KEY POINTS. Learning objectives now added to the beginning of each chapter map to specific end-of-chapter problems for improved instructional design and outcomes tracking. In addition, most problems now have brief, inline descriptions added.

• NEW WEBASSIGN DIGITAL RESOURCES AND VIDEOS GUIDE LEARNING. The most recent edition of WebAssign courseware now offers new chapter overview videos and problem walk-through videos (called "Watch Its") as well as additional resources to improve the depth and breadth of assignments and offer help for students completing homework and quizzes. A new test bank is also available to check student comprehension.

• PROVEN PROBLEM-SCENARIO APPROACH ENSURES COMPREHENSION. A hallmark strength of this text, the authors' unique 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.

• CHAPTER CONTENT AND PROBLEMS ALIGN WITH LEARNING OBJECTIVES. Each chapter includes a list of learning objectives that reflects Bloom's taxonomy. Every end-of-chapter problem now includes a descriptive problem title and lists the learning objectives that correspond to the problem for convenient review.

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

• ROBUST ONLINE CONTENT REINFORCES AND EXPANDS UPON THE BOOK'S THOROUGH EXPLANATIONS. This edition's wealth of digital content provides Excel® templates that correspond with this edition's text examples, models and software.

• INTEGRATED SOFTWARE APPLICATIONS HELP STUDENTS MASTER CRITICAL SKILLS. The edition's hallmark approach integrates coverage of applications with Excel®, helping you equip students with critical problem-solving skills in Excel®.

• REVISIONS, GUIDED BY READER FEEDBACK, FURTHER IMPROVE CONCEPT EXPLANATIONS. Expanded discussions clarify key concepts. For instance, Chapter 7 clearly introduces the feasibility table to aid the construction of conditional and corequisite constraints. Chapter 8 expands discussion of sensitivity analysis for nonlinear optimization, and Chapter 10 clarifies the when-to-order decision for the various inventory models. In addition, Chapter 11 offers revised technical notes on multiple-server queueing systems.

• NEW "MANAGEMENT SCIENCE IN ACTION" VIGNETTES AND PROBLEMS DEMONSTRATE CONCEPTS AT WORK. Six new "Management Science in Action" vignettes describe how material covered in this edition is actually used in practice today. In addition, more than 15 end-of-chapter problems are new and many are updated.

• FULL-COLOR INTERNAL DESIGN APPEALS TO STUDENTS AND HELPS CLARIFY KEY POINTS. Learning objectives now added to the beginning of each chapter map to specific end-of-chapter problems for improved instructional design and outcomes tracking. In addition, most problems now have brief, inline descriptions added.

• NEW WEBASSIGN DIGITAL RESOURCES AND VIDEOS GUIDE LEARNING. The most recent edition of WebAssign courseware now offers new chapter overview videos and problem walk-through videos (called "Watch Its") as well as additional resources to improve the depth and breadth of assignments and offer help for students completing homework and quizzes. A new test bank is also available to check student comprehension.

• PROVEN PROBLEM-SCENARIO APPROACH ENSURES COMPREHENSION. A hallmark strength of this text, the authors' unique 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.

• CHAPTER CONTENT AND PROBLEMS ALIGN WITH LEARNING OBJECTIVES. Each chapter includes a list of learning objectives that reflects Bloom's taxonomy. Every end-of-chapter problem now includes a descriptive problem title and lists the learning objectives that correspond to the problem for convenient review.

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

• ROBUST ONLINE CONTENT REINFORCES AND EXPANDS UPON THE BOOK'S THOROUGH EXPLANATIONS. This edition's wealth of digital content provides Excel® templates that correspond with this edition's text examples, models and software.

• INTEGRATED SOFTWARE APPLICATIONS HELP STUDENTS MASTER CRITICAL SKILLS. The edition's hallmark approach integrates coverage of applications with Excel®, helping you equip students with critical problem-solving skills in Excel®.

Cengage provides a range of supplements that are updated in coordination with the main title selection. For more information about these supplements, contact your Learning Consultant.