Introduction to Linear Optimization and Extensions with MATLAB

Roy H. Kwon

ISBN 10: 143986263X / ISBN 13: 9781439862636

Verlag: CRC Press, 2013

Beschreibung

nach der Bestellung gedruckt Neuware - Printed after ordering - This book fills the need for an introductory book on linear programming that discusses the important ways to mitigate parameter uncertainty. It includes two major ways of including parameter uncertainty: stochastic linear programming and robust linear optimization. Presenting basics before theory, the author offers a rigorous development of linear programming theory and methods. The text contains financial optimization case studies, an extensive bibliography, and MATLAB® exercises, with the code available on the book's CRC Press web page.

Bestandsnummer des Verkäufers 9781439862636

Bibliografische Details

• Titel: Introduction to Linear Optimization and Extensions with MATLAB
• Verlag: CRC Press
• Erscheinungsjahr: 2013
• Sprache: Englisch
• ISBN-10: 143986263X
• ISBN-13: 9781439862636
• Einband: Buch
• Zustand: Neu

Über diesen Titel

Inhaltsangabe

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® 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.

Über die Autorin bzw. den Autor

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