Introduction to Management Science, 3e / Edition 3

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The purpose of this text is to provide the student with a comprehensive coverage of how management science concepts and approaches can be applied to improve management decision-making. The emphasis is on the translation of mathematical modeling concepts into a presentation that is palatable to the undergraduate student of business with limited mathematical background. ManageĀ¬ment science topics are introduced by presenting realistic, practical examples in the form of small case studies. Difficult techniques are presented within the framework of working examples, stressing an intuitive understanding of concepts in the decision support perspective rather than focusing on mathematical techniques for their own sake.
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Product Details

  • ISBN-13: 9780324415995
  • Publisher: Cengage Learning
  • Publication date: 7/11/2005
  • Edition description: New Edition
  • Edition number: 3
  • Pages: 828
  • Sales rank: 1,192,419
  • Product dimensions: 8.40 (w) x 10.70 (h) x 1.30 (d)

Meet the Author

Sang M. Lee is currently the University Eminent Scholar, Regents Distinguished Professor, Chair of the Management Department, Executive Director of the Nebraska Productivity and Entrepreneurship Center, and Director of the Center for Albania Studies. He received his Ph.D. degree in Management from the University of Georgia in 1969. He served as Professor at Virginia Polytechnic Institute and State University prior to coming to the University of Nebraska in 1976. Dr. Lee is currently President of the Pan-Pacific Business Association, an international scholarly society of over 4,000 members in 35 countries. He has organized 26 international conferences as the Program Chair. He is on the editorial board of 23 journals. Dr. Lee is an internationally known expert in the fields of decision sciences, productivity management and global business. His pioneering work in Goal Programming and Multiple Objective Decision Making has been widely recognized throughout the world. He is a Senior Scientist of the Gallup Organization where he advises on global projects.

David L. Olson is the James & H.K. Stuart Professor in MIS and Othmer Professor at the University of Nebraska. He received his Ph.D. in Business from the University of Nebraska in 1981. He has published research in over 80 refereed journal articles, primarily on the topic of multiple objective decision-making. He teaches in the management information systems, management science, and operations management areas. He has authored the books Decision Aids for Selection Problems, Introduction to Information Systems Project Management, and Managerial Issues of Enterprise Resource Planning Systems and co-authored the books Decision Support Models and Expert Systems; Introduction to Management Science; Introduction to Simulation and Risk Analysis; Business Statistics: Quality Information for Decision Analysis; Statistics, Decision Analysis, and Decision Modeling; Multiple Criteria Analysis in Strategic Siting Problems, and Introduction to Business Data Mining. He has made over 100 presentations at international and national conferences on research topics. He is a member of the Association for Information Systems, the Decision Sciences Institute, the Institute for Operations Research and Management Sciences, and the Multiple Criteria Decision Making Society. He has coordinated the Decision Sciences Institute Dissertation Competition, Innovative Education Competition, chaired the Doctoral Affairs Committee, served as nationally elected vice president three times, and as National Program Chair. He was with Texas A&M University from 1981 through 2001, the last two years as Lowry Mays Professor of Business in the Department of Information and Operations Management. He received a Research Fellow Award from the College of Business and Graduate School of Business at Texas A&M University, and held the Business Analysis Faculty Excellence Fellowship for two years. He is a Fellow of the Decision Sciences Institute.

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Table of Contents

Part 1 Introduction Chapter 1: The Role of Management Science Chapter 2: Modeling in Management Science Part 2 Optimization Models Chapter 3: Introduction to Linear Programming Chapter 4: Simplex Method of Linear Programming Chapter 5: Duality, Sensitivity Analysis, and Computer Solutions of Linear Programming Chapter 6: Integer and Zero-one Programming Chapter 7: Goal Programming Chapter 8: The Transportation Problem Chapter 9: The Assignment Problem Chapter 10: Network Models Chapter 11:Nonlinear Programming Part 3 Other Quantitative Techniques Chapter 12: Project Planning with PERT and CPM Chapter 13: Decision Theory Chapter 14: Analytic Hierarchy Process Chapter 15: Inventory Models Chapter 16: Waiting Line (Queuing) Models Chapter 17: Dynamic Programming Chapter 18: Simulation Chapter 19: Forecasting Chapter 20: Markov Analysis Part 4 Relationship to Information Systems Chapter 21:Management Science Implementation and Decision Support Systems Appendix 1: Poisson Probability Values Appendix 2: Values of e x and e -x Appendix 3: Values of Po for Various Combinations of Appendix 4: Area Under the Standard Normal Curve Appendix 5: Table of Random Numbers Author Index Topic Index
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