For over four decades, Introduction to Operations Research has been the classic text on operations research. While building on the classic strengths of the text, the author continues to find new ways to make the text current and relevant to students. One way is by incorporating a wealth of state-of-the art, user-friendly software and more coverage of business applications than ever before. When the first co-author received the prestigious Expository Writing Award from INFORMS for a recent edition, the award citation described the reasons for the book's great success as follows: >"Two features…mehr
For over four decades, Introduction to Operations Research has been the classic text on operations research. While building on the classic strengths of the text, the author continues to find new ways to make the text current and relevant to students. One way is by incorporating a wealth of state-of-the art, user-friendly software and more coverage of business applications than ever before. When the first co-author received the prestigious Expository Writing Award from INFORMS for a recent edition, the award citation described the reasons for the book's great success as follows: >"Two features account for this success. First, the editions have been outstanding from students' points of view due to excellent motivation, clear and intuitive explanations, good examples of professional practice, excellent organization of material, very useful supporting software, and appropriate but not excessive mathematics. Second, the editions have been attractive from instructors' points of view because they repeatedly infuse state-of-the-art material with remarkable lucidity and plain language."Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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. Hillier's 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.
Inhaltsangabe
1) Introduction 2) Overview of How Operations Research and Analytics Professionals Analyze Problems 3) Introduction to Linear Programming 4) Solving Linear Programming Problems: The Simplex Method 5) The Theory of the Simplex Method 6) Duality Theory 7) Linear Programming under Uncertainty 8) Other Algorithms for Linear Programming 9) The Transportation and Assignment Problems 10) Network Optimization Models 11) Dynamic Programming 12) Integer Programming 13) Nonlinear Programming 14) Metaheuristics 15) Game Theory 16) Decision Analysis 17) Queueing Theory 18) Inventory Theory 19) Markov Decision Processes 20) Simulation Appendix 1 - Documentation for the OR Courseware Appendix 2 - Convexity Appendix 3 - Classical Optimization Methods Appendix 4 - Matrices and Matrix Operations Appendix 5 - Table for a Normal Distribution
1) Introduction 2) Overview of How Operations Research and Analytics Professionals Analyze Problems 3) Introduction to Linear Programming 4) Solving Linear Programming Problems: The Simplex Method 5) The Theory of the Simplex Method 6) Duality Theory 7) Linear Programming under Uncertainty 8) Other Algorithms for Linear Programming 9) The Transportation and Assignment Problems 10) Network Optimization Models 11) Dynamic Programming 12) Integer Programming 13) Nonlinear Programming 14) Metaheuristics 15) Game Theory 16) Decision Analysis 17) Queueing Theory 18) Inventory Theory 19) Markov Decision Processes 20) Simulation Appendix 1 - Documentation for the OR Courseware Appendix 2 - Convexity Appendix 3 - Classical Optimization Methods Appendix 4 - Matrices and Matrix Operations Appendix 5 - Table for a Normal Distribution
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