Introduction to Linear Optimization and Extensions with MATLAB®
By Roy H. Kwon
To Be Published July 17th 2013 by CRC Press – 368 pages
Series: Operations Research Series
Filling the need for an introductory book on linear programming that discusses the important ways to mitigate parameter uncertainty, this book includes two major ways of including parameter uncertainty: stochastic linear programming and robust linear optimization. It offers a vigorous development of linear programming theory and methods by presenting basics before theory. It also presents financial optimization case studies that consolidate the material presented within the book. A student solutions manual is provided, as well as MATLAB exercises and code accessible by website. MATLAB exercises, a student solutions manual, and an extensive bibliography are included.
FUNDAMENTALS. Geometry of Linear Optimization. Simplex Method. Duality and Sensitivity Analysis. EXTENSIONS.Decomposition in Linear Optimization. Quadratic Optimization. Interior Point Methods. ROBUST STRATEGIES FOR LINEAR OPTIMIZATION. Stochastic Programming. Robust Linear Optimization.
Roy H Kwon is a professor at University of Toronto - St. George Campus, Canada.