Introduction to Linear Optimization and Extensions with MATLAB® (Operations Research Series)

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9781439862636: Introduction to Linear Optimization and Extensions with MATLAB® (Operations Research Series)
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"The book goes beyond a `cookbook' for linear optimization in Matlab; instead it outlines and explains the theory behind each linear optimization technique and a number of essential theorems are provided and proven. This greatly helps the reader understand why each technique works and how it is implemented in the Matlab software. Computational projects suggested in the book can also assist students with the practical implementation of the techniques in real-life applications.
―Efstratios Rappos (Aubonne) in Zentralblatt, MATH 1287

About the Author:

Roy H Kwon is a professor at University of Toronto - St. George Campus, Canada.

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Roy H. Kwon
Published by Taylor & Francis Inc, United States (2013)
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Book Description Taylor & Francis Inc, United States, 2013. Hardback. Condition: New. Language: English. Brand new Book. Filling the need for an introductory book on linear programming that discusses the important ways to mitigate parameter uncertainty, Introduction to Linear Optimization and Extensions with MATLAB (R) provides a concrete and intuitive yet rigorous introduction to modern linear optimization. In addition to fundamental topics, the book discusses current linear optimization technologies such as predictor-path following interior point methods for both linear and quadratic optimization as well as the inclusion of linear optimization of uncertainty i.e. stochastic programming with recourse and robust optimization. The author introduces both stochastic programming and robust optimization as frameworks to deal with parameter uncertainty. The author's unusual approach-developing these topics in an introductory book-highlights their importance. Since most applications require decisions to be made in the face of uncertainty, the early introduction of these topics facilitates decision making in real world environments. The author also includes applications and case studies from finance and supply chain management that involve the use of MATLAB.Even though there are several LP texts in the marketplace, most do not cover data uncertainty using stochastic programming and robust optimization techniques. Most emphasize the use of MS Excel, while this book uses MATLAB which is the primary tool of many engineers, including financial engineers. The book focuses on state-of-the-art methods for dealing with parameter uncertainty in linear programming, rigorously developing theory and methods. But more importantly, the author's meticulous attention to developing intuition before presenting theory makes the material come alive. Seller Inventory # AA69781439862636

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Roy H. Kwon
Published by Taylor & Francis Inc, United States (2013)
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Book Description Taylor & Francis Inc, United States, 2013. Hardback. Condition: New. Language: English. Brand new Book. Filling the need for an introductory book on linear programming that discusses the important ways to mitigate parameter uncertainty, Introduction to Linear Optimization and Extensions with MATLAB (R) provides a concrete and intuitive yet rigorous introduction to modern linear optimization. In addition to fundamental topics, the book discusses current linear optimization technologies such as predictor-path following interior point methods for both linear and quadratic optimization as well as the inclusion of linear optimization of uncertainty i.e. stochastic programming with recourse and robust optimization. The author introduces both stochastic programming and robust optimization as frameworks to deal with parameter uncertainty. The author's unusual approach-developing these topics in an introductory book-highlights their importance. Since most applications require decisions to be made in the face of uncertainty, the early introduction of these topics facilitates decision making in real world environments. The author also includes applications and case studies from finance and supply chain management that involve the use of MATLAB.Even though there are several LP texts in the marketplace, most do not cover data uncertainty using stochastic programming and robust optimization techniques. Most emphasize the use of MS Excel, while this book uses MATLAB which is the primary tool of many engineers, including financial engineers. The book focuses on state-of-the-art methods for dealing with parameter uncertainty in linear programming, rigorously developing theory and methods. But more importantly, the author's meticulous attention to developing intuition before presenting theory makes the material come alive. Seller Inventory # AA69781439862636

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