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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.