An Introduction to Management Science: Quantitative Approaches to Decision Making, Revised (with Microsoft Project and Printed Access Card) / Edition 13

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Overview


Gain a sound conceptual understanding of the role that management science plays in the decision-making process with the latest edition of the book that has defined today's management science course: Anderson/Sweeney/Williams/Camm/Martin's AN INTRODUCTION TO MANAGEMENT SCIENCE: QUANTITATIVE APPROACHES TO DECISION MAKING, REVISED 13th Edition. The trusted market leader for more than two decades, the new edition now prepares readers for success with the latest developments in Microsoft Office Excel 2010, including data sets, applications and screen visuals throughout that reflect Excel 2010. Readers learn from the book's proven applications-oriented approach, powerful examples, and problem-scenario approach that introduces each quantitative technique within an applications setting. Readers can get a copy of LINGO software and Excel add-ins with the book's online content. A copy of the popular Microsoft Project Professional 2010 accompanies the book on CD.
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Product Details

  • ISBN-13: 9781111532222
  • Publisher: Cengage Learning
  • Publication date: 3/4/2011
  • Edition description: Revised
  • Edition number: 13
  • Pages: 896
  • Sales rank: 173,150
  • Product dimensions: 7.44 (w) x 9.69 (h) x 0.79 (d)

Meet the Author


Dr. David R. Anderson is a textbook author and Professor Emeritus of Quantitative Analysis in the College of Business Administration at the University of Cincinnati. He 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 has taught graduate-level courses in regression analysis, multivariate analysis, and management science. He also has taught statistical courses at the Department of Labor in Washington, D.C. Professor Anderson has received numerous honors for excellence in teaching and service to student organizations. He is the coauthor of ten textbooks related to decision sciences and actively consults with businesses in the areas of sampling and statistical methods. Born in Grand Forks, North Dakota, he earned his BS, MS, and PhD degrees from Purdue University.

Dr. Dennis J. Sweeney is a textbook author, Professor Emeritus of Quantitative Analysis and founder of the Center for Productivity Improvement at the University of Cincinnati. He also served five years as head of the Department of Quantitative Analysis and four years as Associate Dean of the College of Business Administration. In addition, he has worked in the management science group at Procter & Gamble and has been a visiting professor at Duke University. Professor Sweeney has published more than 30 articles 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 MANAGEMENT SCIENCE, OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING, DECISION SCIENCES, and other journals. Dr. Sweeney is the coauthor of ten textbooks in the areas of statistics, management science, linear programming, and production and operations management. Born in Des Moines, Iowa, he earned a BS degree from Drake University, graduating summa cum laude. He received his MBA and DBA degrees from Indiana University, where he was an NDEA Fellow.

Dr. Thomas A. Williams is a textbook author and Professor Emeritus of Management Science in the College of Business at Rochester Institute of Technology, where he was the first chair of the Decision Sciences Department. Before joining RIT, he served for seven years as a faculty member in the College of Business Administration at the University of Cincinnati, where he developed the first undergraduate program in Information Systems. Dr. Williams is the coauthor of 11 textbooks in the areas of management science, statistics, production and operations management, and mathematics. He has been a consultant for numerous Fortune 500 companies in areas ranging from the use of elementary data analysis to the development of large-scale regression models. Born in Elmira, New York, he earned his BS degree at Clarkson University and his MS and PhD at Rensselaer Polytechnic Institute.

Dr. Jeffrey D. Camm is Professor of Quantitative Analysis and head of the Department of Quantitative Analysis and Operations Management at the University of Cincinnati, where he has been since 1984. He also has served as 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 30 papers in the general area of optimization applied to problems in operations management, and his research has been funded by the Air Force Office of Scientific Research, The Office of Naval Research, and the U.S. Department of Energy. Among his honors, he was named the Dornoff Fellow of Teaching Excellence and received the 2006 INFORMS Prize for the Teaching of Operations Research Practice. Dr. Camm currently serves as editor-in-chief of INTERFACES and is on the editorial board of INFORMS TRANSACTIONS ON EDUCATION. He received his PhD in Management Science from Clemson University.

Dr. Kipp Martin is Professor of Operations Research and Computing Technology at the Graduate School of Business, University of Chicago. Born in St. Bernard, Ohio, he earned a B.A. in Mathematics, an MBA, and a Ph.D. in Management Science from the University of Cincinnati. While at the University of Chicago, Professor Martin has taught courses in Management Science, Operations Management, Business Mathematics, and Information Systems. Research interests include incorporating Web technologies such as XML, XSLT, XQuery, and Web Services into the mathematical modeling process; the theory of how to construct good mixed integer linear programming models; symbolic optimization; polyhedral combinatorics; methods for large scale optimization; bundle pricing models; computing technology and database theory. Dr. Martin has published in INFORMS Journal of Computing, Management Science, Mathematical Programming, Operations Research, The Journal of Accounting Research, and other professional journals. He is also the author of The Essential Guide to Internet Business Technology (with Gail Honda) and Large Scale Linear and Integer Optimization.

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Table of Contents


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. Forecasting. 16. Markov Processes. 17. Linear Programming: Simplex Method (on Website). 18. Simplex-Based Sensitivity Analysis and Duality (on Website). 19. Solution Procedures for Transportation (on Website). 20. Minimal Spanning Tree (on Website). 21. Dynamic Programming (on Website).
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