This book provides an original treatment of robust (RO) and adaptive robust optimization (ARO) based on over twenty years of research by each of the authors. Structure of the Book Part I describes linear RO and the underlying uncertainty sets. Part II treats modeling, exact and approximate algorithms for ARO. Part III introduces nonlinear RO for concave uncertainty. Part IV outlines nonlinear RO for concave uncertainty. Part V discusses the theory of distributional RO and ARO. Part VI contains a variety of RO and ARO applications including queueing theory, auction design, option pricing and energy unit commitment. ORIGINAL CHARACTERISTICS OF THE Emphasis on modeling in RO and ARO. Integrated treatment of RO and ARO and of nonlinear RO for concave and convex uncertainty, as opposed to robust conic optimization. Interplay of probability theory to select parameters in RO and of optimization for tractability.