Introduction to Management Science: Quantative Approaches to Decision Making (2nd Revised edition)

Introduction to Management Science: Quantative Approaches to Decision Making (2nd Revised edition)

By: Dennis Sweeney (author), Mik Wisniewski (author), Thomas Arthur Williams (author), David Anderson (author)Mixed Media

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In the second edition of this highly-regarded text, the accessible application-driven approach that made the first edition so successful has been retained, whilst it has been streamlined and strengthened further to meet the needs of students across the UK, Europe, Middle East and Africa. Packed with diverse realistic examples from Scotland to Saudi Arabia, this truly internationalized version of the landmark text from the Anderson, Sweeney and Williams team provides a comprehensive introduction to the subjects of Management Science and Operations Research.

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About Author

Dr. Thomas A. Williams is Professor of Management Science in the College of Business at Rochester Institute of Technology where he was the first chairman of the Decision Sciences Department. He teaches courses in management science and statistics, as well as graduate courses in regression and decision analysis. Before joining the College of Business at RIT, Professor Williams served for seven years as a faculty member in the College of Business Administration at the University of Cincinnati, where he developed the undergraduate program in Information Systems and then served as its coordinator. The co-author of 11 leading textbooks in the areas of management science, statistics, production and operations management, and mathematics, Professor Williams has been a consultant for numerous Fortune 500 companies and has worked on projects ranging from the use of data analysis to the development of large-scale regression models. He earned his B.S. degree at Clarkson University and completed his graduate work at Rensselaer Polytechnic Institute, where he received his M.S. and Ph.D. degrees. 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. David R. Anderson is Professor of Quantitative Analysis in the College of Business Administration at the University of Cincinnati, USA. Mik Wisniewski is Senior Research Fellow in the Management Science department at Strathclyde Business School, Glasgow, Scotland. He is author of over a dozen texts on management science, quantitative business analysis and optimisation, including the established Quantitative Methods for Decision Makers (Pearson), and has many published articles in these areas. Mik also runs his own consulting company and clients including Shell, KPMG, PriceWaterhouseCoopers, numerous government agencies both in the UK and overseas, and a range of public sector organisations. He as worked extensively across Europe, the Middle East, Africa and Asia.


1. Introduction 2. An Introduction to Linear Programming 3. Linear Programming: Sensitivity Analysis and Interpretation of Solution 4. Linear Programming Applications 5. Linear Programming: The Simplex Method 6. Simplex-Based Sensitivity Analysis and Duality 7. Transportation, Assignment, and Transshipment Problems 8. Network Models 9. Project Scheduling: PERT/CPM 10. Inventory Models 11. Queuing Models 12. Simulation 13. Decision Analysis 14. Multicriteria Decisions Conclusion: Management Science in Practice Appendix A: Areas for the Standard Normal Distribution Appendix B: Values of e l Appendix C: Bibliography and References Appendix D: Self-Test Solutions Glossary Online Contents 15. Integer Linear Programming 16. Forecasting 17. Dynamic Programming 18. Markov Processes

Product Details

  • publication date: 07/05/2014
  • ISBN13: 9781408088401
  • Format: Mixed Media
  • Number Of Pages: 672
  • ID: 9781408088401
  • weight: 1305
  • ISBN10: 1408088401
  • edition: 2nd Revised edition

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