
Introduction to Management Science: A Modeling and Case Studies Approach with Spreadsheets
McGraw Hill Higher Education (Publisher)
4th Edition
Published on 16. July 2010
Book
Mixed media product
640 pages
978-0-07-128931-3 (ISBN)
Article exhausted; check for reprint
Description
Introduction to Management Science, 4e, offers a unique model approach and integrates the use of Excel. Through this approach students are better able to grasp the essential concepts covered in the course and see their utility. 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. These cases and related applications cut across all functional areas of business and show how management science techniques apply in the business environment.
More details
Edition
4th edition
Language
English
Place of publication
London
United States
Publishing group
McGraw-Hill Education - Europe
Target group
College/higher education
Dimensions
Height: 278 mm
Width: 218 mm
Thickness: 24 mm
Weight
1344 gr
ISBN-13
978-0-07-128931-3 (9780071289313)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
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Frederick Hillier | Mark Hillier
ISE Introduction to Management Science: A Modeling and Case Studies Approach with Spreadsheets
A Modeling and Case Studies Approach with Spreadsheets
Book
01/2018
6th Edition
McGraw-Hill Education
€61.41
Article is exhausted; no reprint
Persons
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.
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.
Content
Chapter 1: Introduction Chapter 2: Linear Programming: Basic Concepts Chapter 3: Linear Programming: Formulation and Applications Chapter 4: The Art of Modeling with Spreadsheets Chapter 5: What-If Analysis for Linear Programming Chapter 6: Network Optimization Problems Chapter 7: Using Binary Integer Programming to Deal with Yes-or-No Decisions Chapter 8: Nonlinear Programming Chapter 9: Decision Analysis Chapter 10: Forecasting Chapter 11: Queueing Models Chapter 12: Computer Simulation: Basic Concepts Chapter 13: Computer Simulation with Crystal Ball Appendix A: Using the Solver Table Appendix B: Tips for Using Microsoft Excel for Modeling Appendix C: Partial Answers to Selected Problems Supplements on the CD-ROM: Supplement to Chapter 2: More about the Graphical Method for Linear Programming Supplement to Chapter 5: Reduced Costs Supplement to Chapter 6: Minimum Spanning-Tree Problems Supplement 1 to Chapter 7: Advanced Formulation Techniques for Binary Integer Programming Supplement 2 to Chapter 7: Some Perspectives on Solving Binary Integer Programming Problems Supplement to Chapter 9: Decision Criteria Supplement to Chapter 10: Time-Series Forecasting with CB Predictor Supplement to Chapter 11: Additional Queueing Models Supplement to Chapter 12: The Inverse Transformation Method for Generating Random Observations Chapters on the CD-ROM: Chapter 14: Solution Concepts for Linear Programming Chapter 15: Transportation and Assignment Problems Chapter 16: PERT/CPM Models for Project Management Chapter 17: Goal Programming Chapter 18: Inventory Management with Known Demand Chapter 19: Inventory Management with Uncertain Demand