Introductory management science
Author(s)
Bibliographic Information
Introductory management science
Prentice Hall, c1993
4th ed.
Available at 10 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
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  Tokyo
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  Toyama
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  Kyoto
  Osaka
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  Shimane
  Okayama
  Hiroshima
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  Tokushima
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  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
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  United Kingdom
  Germany
  Switzerland
  France
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  Netherlands
  Sweden
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  United States of America
Note
Diskette (3 3/4 inch) entitled 'LINDO student version' enclosed inside back cover in pocket
Includes index
Description and Table of Contents
Description
This highly-esteemed text introduces readers to the key ideas of management science that will be important to them throughout their careers. Addressing the needs of readers interested in both management science and business administration careers, the book emphasizes the role of management science techniques in the larger context of business decision-making. There is a strong focus on models-how they are created, how they are used, what kinds of insights they provide-and on the critical importance of managerial judgement in utilizing those insights. At the same time, for readers interested in more technical aspects of the subject, there is an unparalleled treatment of linear programming techniques. Computer applications, including the use of spreadsheets and of many popular special-purpose software packages, are integrated throughout the text in great abundance.
Table of Contents
(NOTE: At the End of Each Chapter is a Video Case.) 1. Introduction: Models and Modeling. I: DETERMINISTIC MODELS. 2. Linear Programming: Formal and Spreadsheet Models. 3. Linear Programming: Geometric Representations and Graphical Solutions. 4. Analysis of LP Models: The Graphical Approach. 5. Linear Programs: Computer Analysis, Interpreting Sensitivity Output, and the Dual Problem. 6. Linear Programming: The Simplex Method. 7. Linear Programming: Special Applications. 8. Integer and Quadratic Programming. 9. Network Models. 10. Inventory Control with Known Demand. 11. Heuristics, Multiple Objectives, and Goal Programming. 12. Calculus-Based Optimization and an Introduction to Nonlinear Programming. II: PROBABILISTIC MODELS. 13. Simulation. 14. Decision Theory and Decision Trees. 15. Project Management: PERT and CPM. 16. Inventory Models with Probabilistic Demand. 17. Queuing Models. 18. Forecasting. Answers to Odd-Numbered Problems. Appendix A: Basic Concepts in Probability. Using LINDO. Index.
by "Nielsen BookData"