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9780072833478: Introduction to Management Science w/ Student CD-ROM

Synopsis

Introduction to Management Science, 2e offers a unique case study approach and integrates the use of Excel. Each chapter includes a case study that is meant to show the students a real and interesting application of the topics addressed in that chapter. This most recent revision has been thoroughly updated to be more “user-friendly” and more technologically advanced. These changes include, a completely new chapter on the art of modeling with spreadsheets. This unique chapter goes far beyond anything found in other textbooks and are based on the award winning methodologies used by Mark Hillier in his own course. The technology package has also been greatly enhanced to include, Crystal Ball 2000 (Professional Edition) a Management Science Online Learning Center, and an Excel add-in called Alver Table for performing sensitivity analysis. Crystal Ball is the most popular Excel add-in for computer simulation and includes OptQuest (an optimizer with simulation) as well as a forecasting module. The Management Science Online Learning Center (website) includes several modules that enable students to interactively explore certain management science techniques in depth. Solver Table is an Excel add-in developed by the author to help perform sensitivity analysis systematically, as well as substantially expanded coverage of computer simulation, including Crystal Ball. We now have two chapters on computer simulation instead of one, where the second chapter features the use of Crystal Ball.all.

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About the Authors

Professor emeritus of operations research at Stanford University. Dr. Hillier is especially known for his classic, award-winning text, Introduction to Operations Research, co-authored with the late Gerald J. Lieberman, which has been translated into well over a dozen languages and is currently in its 8th edition. The 6th edition won honorable mention for the 1995 Lanchester Prize (best English-language publication of any kind in the field) and Dr. Hillier also was awarded the 2004 INFORMS Expository Writing Award for the 8th edition. His other books include The Evaluation of Risky Interrelated Investments, Queueing Tables and Graphs, Introduction to Stochastic Models in Operations Research, and Introduction to Mathematical Programming. He received his BS in industrial engineering and doctorate specializing in operations research and management science from Stanford University. The winner of many awards in high school and college for writing, mathematics, debate, and music, he ranked first in his undergraduate engineering class and was awarded three national fellowships (National Science Foundation, Tau Beta Pi, and Danforth) for graduate study. Dr. Hilliers research has extended into a variety of areas, including integer programming, queueing theory and its application, statistical quality control, and production and operations management. He also has won a major prize for research in capital budgeting.

Associate professor of quantitative methods at the School of Business at the University of Washington. Dr. Hillier received his BS in engineering (plus a concentration in computer science) from Swarthmore College, and he received his MS with distinction in operations research and PhD in industrial engineering and engineering management from Stanford University. As an undergraduate, he won the McCabe Award for ranking first in his engineering class, won election to Phi Beta Kappa based on his work in mathematics, set school records on the mens swim team, and was awarded two national fellowships (National Science Foundation and Tau Beta Pi) for graduate study. During that time, he also developed a comprehensive software tutorial package, OR Courseware, for the Hillier-Lieberman textbook, Introduction to Operations Research. As a graduate student, he taught a PhD-level seminar in operations management at Stanford and won a national prize for work based on his PhD dissertation. At the University of Washington, he currently teaches courses in management science and spreadsheet modeling.

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