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^(R) exercises, with the code available on the book's CRC Press web page.

� propos de l?auteur

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

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