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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A Modeling Approach: The entire book revolves around modeling as an aid to managerial decision making. Rather than spending substantial time on algorithms, the mechanics of procedures, or the manipulation of spreadsheets, the focus is on the art of model formulation, the role of a model, and the analysis of model results. A wide-range of model types is considered.
A Case Studies Approach: Many of the chapters feature at least one case study that introduces and illustrates the application of that chapter's techniques in a realistic setting. (In a few cases, the entire chapter revolves around a case study.) These cases also convey the whole process of a management science study, some of the pitfalls involved, and the complementary roles of the management science team and that manager responsible for the decisions to be made. The cases at the end of the chapters then enable the instructor to continue the case study process.
An Emphasis on Applications: An unusually heavy emphasis is placed on conveying the diversity of application areas for the various models and techniques. These application areas cut across the spectrum of the functional areas of business that the students are studying in their other courses.
Full Integration of Management Science Success Stories: Many of the other MS books now include vignettes of management science success stories in boxes separated form the text. Rather than setting them apart as interesting curiosities, this book fully integrates them into the text to illustrate certain types of applications in realistic settings.
Further Descriptions of What is Happening In Practice: In addition to these success stories, attention is given to the status of the practice of management science in general. What size of problems is being solved? Which models and techniques are being used most widely? What are their shortcomings and what new developments are beginning to address these shortcomings?
A Managerial Perspective: The students typically are future managers, so the focus is on teaching what an enlightened future manager needs to learn from a management science course rather than trying to train technical analysts.
Strong Motivation: Through all the above features that link the course to the reality of the student's future career would, strong evidence is provided about the relevance and power of management science.
Minimum Prerequisites: The book has been written with a typical business student's vocabulary, background, and attitudes very much in mind. Therefore, the book is directed at a student with little or no college mathematics who is both skeptical and apprehensive about a mathematical approach to decision making. All unnecessary mathematical symbolism and terminology have been eliminated. The only necessary prerequisites are algebra at a pre-calculus level and, for the later chapters, a brief introduction to probability theory. Some familiarity with spreadsheets also is preferable.
Review Questions At the End of Each Section: Several review questions at the end of each section help the student identify the key material from the section. The instructor also has the option of using the questions for homework, lecture material, and class discussion.
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.
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