Robust Optimization

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Publisher : Princeton University Press
ISBN 13 : 1400831059
Total Pages : 565 pages
Book Rating : 4.4/5 (8 download)

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Book Synopsis Robust Optimization by : Aharon Ben-Tal

Download or read book Robust Optimization written by Aharon Ben-Tal and published by Princeton University Press. This book was released on 2009-08-10 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology. Written by the principal developers of robust optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject. Robust optimization is designed to meet some major challenges associated with uncertainty-affected optimization problems: to operate under lack of full information on the nature of uncertainty; to model the problem in a form that can be solved efficiently; and to provide guarantees about the performance of the solution. The book starts with a relatively simple treatment of uncertain linear programming, proceeding with a deep analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach. It then develops the robust optimization theory for uncertain conic quadratic and semidefinite optimization problems and dynamic (multistage) problems. The theory is supported by numerous examples and computational illustrations. An essential book for anyone working on optimization and decision making under uncertainty, Robust Optimization also makes an ideal graduate textbook on the subject.

Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization

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Author :
Publisher : BoD – Books on Demand
ISBN 13 : 1789233283
Total Pages : 71 pages
Book Rating : 4.7/5 (892 download)

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Book Synopsis Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization by : Javier Del Ser Lorente

Download or read book Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization written by Javier Del Ser Lorente and published by BoD – Books on Demand. This book was released on 2018-07-18 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nature-inspired algorithms have a great popularity in the current scientific community, being the focused scope of many research contributions in the literature year by year. The rationale behind the acquired momentum by this broad family of methods lies on their outstanding performance evinced in hundreds of research fields and problem instances. This book gravitates on the development of nature-inspired methods and their application to stochastic, dynamic and robust optimization. Topics covered by this book include the design and development of evolutionary algorithms, bio-inspired metaheuristics, or memetic methods, with empirical, innovative findings when used in different subfields of mathematical optimization, such as stochastic, dynamic, multimodal and robust optimization, as well as noisy optimization and dynamic and constraint satisfaction problems.

Real-time PDE-constrained Optimization

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Publisher : SIAM
ISBN 13 : 9780898718935
Total Pages : 335 pages
Book Rating : 4.7/5 (189 download)

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Book Synopsis Real-time PDE-constrained Optimization by : Lorenz T. Biegler

Download or read book Real-time PDE-constrained Optimization written by Lorenz T. Biegler and published by SIAM. This book was released on 2007-01-01 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many engineering and scientific problems in design, control, and parameter estimation can be formulated as optimization problems that are governed by partial differential equations (PDEs). The complexities of the PDEs--and the requirement for rapid solution--pose significant difficulties. A particularly challenging class of PDE-constrained optimization problems is characterized by the need for real-time solution, i.e., in time scales that are sufficiently rapid to support simulation-based decision making. Real-Time PDE-Constrained Optimization, the first book devoted to real-time optimization for systems governed by PDEs, focuses on new formulations, methods, and algorithms needed to facilitate real-time, PDE-constrained optimization. In addition to presenting state-of-the-art algorithms and formulations, the text illustrates these algorithms with a diverse set of applications that includes problems in the areas of aerodynamics, biology, fluid dynamics, medicine, chemical processes, homeland security, and structural dynamics. Audience: readers who have expertise in simulation and are interested in incorporating optimization into their simulations, who have expertise in numerical optimization and are interested in adapting optimization methods to the class of infinite-dimensional simulation problems, or who have worked in "offline" optimization contexts and are interested in moving to "online" optimization.

Resource-Constrained Project Scheduling

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Publisher : John Wiley & Sons
ISBN 13 : 1118623703
Total Pages : 235 pages
Book Rating : 4.1/5 (186 download)

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Book Synopsis Resource-Constrained Project Scheduling by : Christian Artigues

Download or read book Resource-Constrained Project Scheduling written by Christian Artigues and published by John Wiley & Sons. This book was released on 2013-03-01 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: This title presents a large variety of models and algorithms dedicated to the resource-constrained project scheduling problem (RCPSP), which aims at scheduling at minimal duration a set of activities subject to precedence constraints and limited resource availabilities. In the first part, the standard variant of RCPSP is presented and analyzed as a combinatorial optimization problem. Constraint programming and integer linear programming formulations are given. Relaxations based on these formulations and also on related scheduling problems are presented. Exact methods and heuristics are surveyed. Computational experiments, aiming at providing an empirical insight on the difficulty of the problem, are provided. The second part of the book focuses on several other variants of the RCPSP and on their solution methods. Each variant takes account of real-life characteristics which are not considered in the standard version, such as possible interruptions of activities, production and consumption of resources, cost-based approaches and uncertainty considerations. The last part presents industrial case studies where the RCPSP plays a central part. Applications are presented in various domains such as assembly shop and rolling ingots production scheduling, project management in information technology companies and instruction scheduling for VLIW processor architectures.

Robust Portfolio Optimization and Management

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Publisher : John Wiley & Sons
ISBN 13 : 0470164891
Total Pages : 513 pages
Book Rating : 4.4/5 (71 download)

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Book Synopsis Robust Portfolio Optimization and Management by : Frank J. Fabozzi

Download or read book Robust Portfolio Optimization and Management written by Frank J. Fabozzi and published by John Wiley & Sons. This book was released on 2007-04-27 with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for Robust Portfolio Optimization and Management "In the half century since Harry Markowitz introduced his elegant theory for selecting portfolios, investors and scholars have extended and refined its application to a wide range of real-world problems, culminating in the contents of this masterful book. Fabozzi, Kolm, Pachamanova, and Focardi deserve high praise for producing a technically rigorous yet remarkably accessible guide to the latest advances in portfolio construction." --Mark Kritzman, President and CEO, Windham Capital Management, LLC "The topic of robust optimization (RO) has become 'hot' over the past several years, especially in real-world financial applications. This interest has been sparked, in part, by practitioners who implemented classical portfolio models for asset allocation without considering estimation and model robustness a part of their overall allocation methodology, and experienced poor performance. Anyone interested in these developments ought to own a copy of this book. The authors cover the recent developments of the RO area in an intuitive, easy-to-read manner, provide numerous examples, and discuss practical considerations. I highly recommend this book to finance professionals and students alike." --John M. Mulvey, Professor of Operations Research and Financial Engineering, Princeton University

Iterative Solution Methods

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Publisher : Cambridge University Press
ISBN 13 : 9780521555692
Total Pages : 676 pages
Book Rating : 4.5/5 (556 download)

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Book Synopsis Iterative Solution Methods by : Owe Axelsson

Download or read book Iterative Solution Methods written by Owe Axelsson and published by Cambridge University Press. This book was released on 1996-03-29 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals primarily with the numerical solution of linear systems of equations by iterative methods. The first part of the book is intended to serve as a textbook for a numerical linear algebra course. The material assumes the reader has a basic knowledge of linear algebra, such as set theory and matrix algebra, however it is demanding for students who are not afraid of theory. To assist the reader, the more difficult passages have been marked, the definitions for each chapter are collected at the beginning of the chapter, and numerous exercises are included throughout the text. The second part of the book serves as a monograph introducing recent results in the iterative solution of linear systems, mainly using preconditioned conjugate gradient methods. This book should be a valuable resource for students and researchers alike wishing to learn more about iterative methods.

Convex Optimization

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Publisher : Cambridge University Press
ISBN 13 : 9780521833783
Total Pages : 744 pages
Book Rating : 4.8/5 (337 download)

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Book Synopsis Convex Optimization by : Stephen P. Boyd

Download or read book Convex Optimization written by Stephen P. Boyd and published by Cambridge University Press. This book was released on 2004-03-08 with total page 744 pages. Available in PDF, EPUB and Kindle. Book excerpt: Convex optimization problems arise frequently in many different fields. This book provides a comprehensive introduction to the subject, and shows in detail how such problems can be solved numerically with great efficiency. The book begins with the basic elements of convex sets and functions, and then describes various classes of convex optimization problems. Duality and approximation techniques are then covered, as are statistical estimation techniques. Various geometrical problems are then presented, and there is detailed discussion of unconstrained and constrained minimization problems, and interior-point methods. The focus of the book is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. It contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance and economics.

Optimization

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Publisher : Princeton University Press
ISBN 13 : 1400829364
Total Pages : 683 pages
Book Rating : 4.4/5 (8 download)

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Book Synopsis Optimization by : Jan Brinkhuis

Download or read book Optimization written by Jan Brinkhuis and published by Princeton University Press. This book was released on 2011-02-11 with total page 683 pages. Available in PDF, EPUB and Kindle. Book excerpt: This self-contained textbook is an informal introduction to optimization through the use of numerous illustrations and applications. The focus is on analytically solving optimization problems with a finite number of continuous variables. In addition, the authors provide introductions to classical and modern numerical methods of optimization and to dynamic optimization. The book's overarching point is that most problems may be solved by the direct application of the theorems of Fermat, Lagrange, and Weierstrass. The authors show how the intuition for each of the theoretical results can be supported by simple geometric figures. They include numerous applications through the use of varied classical and practical problems. Even experts may find some of these applications truly surprising. A basic mathematical knowledge is sufficient to understand the topics covered in this book. More advanced readers, even experts, will be surprised to see how all main results can be grounded on the Fermat-Lagrange theorem. The book can be used for courses on continuous optimization, from introductory to advanced, for any field for which optimization is relevant.

First-order and Stochastic Optimization Methods for Machine Learning

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Author :
Publisher : Springer Nature
ISBN 13 : 3030395685
Total Pages : 591 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis First-order and Stochastic Optimization Methods for Machine Learning by : Guanghui Lan

Download or read book First-order and Stochastic Optimization Methods for Machine Learning written by Guanghui Lan and published by Springer Nature. This book was released on 2020-05-15 with total page 591 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms. In spite of the intensive research and development in this area, there does not exist a systematic treatment to introduce the fundamental concepts and recent progresses on machine learning algorithms, especially on those based on stochastic optimization methods, randomized algorithms, nonconvex optimization, distributed and online learning, and projection free methods. This book will benefit the broad audience in the area of machine learning, artificial intelligence and mathematical programming community by presenting these recent developments in a tutorial style, starting from the basic building blocks to the most carefully designed and complicated algorithms for machine learning.

Advances and Trends in Optimization with Engineering Applications

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Publisher : SIAM
ISBN 13 : 1611974674
Total Pages : 730 pages
Book Rating : 4.6/5 (119 download)

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Book Synopsis Advances and Trends in Optimization with Engineering Applications by : Tamas Terlaky

Download or read book Advances and Trends in Optimization with Engineering Applications written by Tamas Terlaky and published by SIAM. This book was released on 2017-04-26 with total page 730 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization is of critical importance in engineering. Engineers constantly strive for the best possible solutions, the most economical use of limited resources, and the greatest efficiency. As system complexity increases, these goals mandate the use of state-of-the-art optimization techniques. In recent years, the theory and methodology of optimization have seen revolutionary improvements. Moreover, the exponential growth in computational power, along with the availability of multicore computing with virtually unlimited memory and storage capacity, has fundamentally changed what engineers can do to optimize their designs. This is a two-way process: engineers benefit from developments in optimization methodology, and challenging new classes of optimization problems arise from novel engineering applications. Advances and Trends in Optimization with Engineering Applications reviews 10 major areas of optimization and related engineering applications, providing a broad summary of state-of-the-art optimization techniques most important to engineering practice. Each part provides a clear overview of a specific area and discusses a range of real-world problems. The book provides a solid foundation for engineers and mathematical optimizers alike who want to understand the importance of optimization methods to engineering and the capabilities of these methods.

Handbook of Research on Predictive Modeling and Optimization Methods in Science and Engineering

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Publisher : IGI Global
ISBN 13 : 1522547673
Total Pages : 644 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Handbook of Research on Predictive Modeling and Optimization Methods in Science and Engineering by : Kim, Dookie

Download or read book Handbook of Research on Predictive Modeling and Optimization Methods in Science and Engineering written by Kim, Dookie and published by IGI Global. This book was released on 2018-06-15 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt: The disciplines of science and engineering rely heavily on the forecasting of prospective constraints for concepts that have not yet been proven to exist, especially in areas such as artificial intelligence. Obtaining quality solutions to the problems presented becomes increasingly difficult due to the number of steps required to sift through the possible solutions, and the ability to solve such problems relies on the recognition of patterns and the categorization of data into specific sets. Predictive modeling and optimization methods allow unknown events to be categorized based on statistics and classifiers input by researchers. The Handbook of Research on Predictive Modeling and Optimization Methods in Science and Engineering is a critical reference source that provides comprehensive information on the use of optimization techniques and predictive models to solve real-life engineering and science problems. Through discussions on techniques such as robust design optimization, water level prediction, and the prediction of human actions, this publication identifies solutions to developing problems and new solutions for existing problems, making this publication a valuable resource for engineers, researchers, graduate students, and other professionals.

Control and Optimization with Differential-Algebraic Constraints

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Publisher : SIAM
ISBN 13 : 1611972248
Total Pages : 351 pages
Book Rating : 4.6/5 (119 download)

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Book Synopsis Control and Optimization with Differential-Algebraic Constraints by : Lorenz T. Biegler

Download or read book Control and Optimization with Differential-Algebraic Constraints written by Lorenz T. Biegler and published by SIAM. This book was released on 2012-11-01 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: A cutting-edge guide to modelling complex systems with differential-algebraic equations, suitable for applied mathematicians, engineers and computational scientists.

Modern Trends in Research on Steel, Aluminium and Composite Structures

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Publisher : Routledge
ISBN 13 : 1000459527
Total Pages : 689 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Modern Trends in Research on Steel, Aluminium and Composite Structures by : Marian A. Giżejowski

Download or read book Modern Trends in Research on Steel, Aluminium and Composite Structures written by Marian A. Giżejowski and published by Routledge. This book was released on 2021-06-09 with total page 689 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern Trends in Research on Steel, Aluminium and Composite Structures includes papers presented at the 14th International Conference on Metal Structures 2021 (ICMS 2021, Poznań, Poland, 16-18 June 2021). The 14th ICMS summarised a few years’ theoretical, numerical and experimental research on steel, aluminium and composite structures, and presented new concepts. This book contains six plenary lectures and all the individual papers presented during the Conference. Seven plenary lectures were presented at the Conference, including "Research developments on glass structures under extreme loads", Parhp3D – The parallel MPI/openMPI implementation of the 3D hp-adaptive FE code", "Design of beam-to-column steel-concrete composite joints: from Eurocodes and beyond", "Stainless steel structures – research, codification and practice", "Testing, modelling and design of bolted joints – effect of size, structural properties, integrity and robustness", "Design of hybrid beam-to-column joints between RHS tubular columns and I-section beams" and "Selected aspects of designing the cold-formed steel structures". The individual contributions delivered by authors covered a wide variety of topics: – Advanced analysis and direct methods of design, – Cold-formed elements and structures, – Composite structures, – Engineering structures, – Joints and connections, – Structural stability and integrity, – Structural steel, metallurgy, durability and behaviour in fire. Modern Trends in Research on Steel, Aluminium and Composite Structures is a useful reference source for academic researchers, graduate students as well as designers and fabricators.

Iterative Methods for Optimization

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Publisher : SIAM
ISBN 13 : 9781611970920
Total Pages : 195 pages
Book Rating : 4.9/5 (79 download)

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Book Synopsis Iterative Methods for Optimization by : C. T. Kelley

Download or read book Iterative Methods for Optimization written by C. T. Kelley and published by SIAM. This book was released on 1999-01-01 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a carefully selected group of methods for unconstrained and bound constrained optimization problems and analyzes them in depth both theoretically and algorithmically. It focuses on clarity in algorithmic description and analysis rather than generality, and while it provides pointers to the literature for the most general theoretical results and robust software, the author thinks it is more important that readers have a complete understanding of special cases that convey essential ideas. A companion to Kelley's book, Iterative Methods for Linear and Nonlinear Equations (SIAM, 1995), this book contains many exercises and examples and can be used as a text, a tutorial for self-study, or a reference. Iterative Methods for Optimization does more than cover traditional gradient-based optimization: it is the first book to treat sampling methods, including the Hooke-Jeeves, implicit filtering, MDS, and Nelder-Mead schemes in a unified way, and also the first book to make connections between sampling methods and the traditional gradient-methods. Each of the main algorithms in the text is described in pseudocode, and a collection of MATLAB codes is available. Thus, readers can experiment with the algorithms in an easy way as well as implement them in other languages.

Lectures on Modern Convex Optimization

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Publisher : SIAM
ISBN 13 : 0898714915
Total Pages : 500 pages
Book Rating : 4.8/5 (987 download)

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Book Synopsis Lectures on Modern Convex Optimization by : Aharon Ben-Tal

Download or read book Lectures on Modern Convex Optimization written by Aharon Ben-Tal and published by SIAM. This book was released on 2001-01-01 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here is a book devoted to well-structured and thus efficiently solvable convex optimization problems, with emphasis on conic quadratic and semidefinite programming. The authors present the basic theory underlying these problems as well as their numerous applications in engineering, including synthesis of filters, Lyapunov stability analysis, and structural design. The authors also discuss the complexity issues and provide an overview of the basic theory of state-of-the-art polynomial time interior point methods for linear, conic quadratic, and semidefinite programming. The book's focus on well-structured convex problems in conic form allows for unified theoretical and algorithmical treatment of a wide spectrum of important optimization problems arising in applications.

Lectures on Stochastic Programming

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Publisher : SIAM
ISBN 13 : 0898718759
Total Pages : 447 pages
Book Rating : 4.8/5 (987 download)

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Book Synopsis Lectures on Stochastic Programming by : Alexander Shapiro

Download or read book Lectures on Stochastic Programming written by Alexander Shapiro and published by SIAM. This book was released on 2009-01-01 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization problems involving stochastic models occur in almost all areas of science and engineering, such as telecommunications, medicine, and finance. Their existence compels a need for rigorous ways of formulating, analyzing, and solving such problems. This book focuses on optimization problems involving uncertain parameters and covers the theoretical foundations and recent advances in areas where stochastic models are available. Readers will find coverage of the basic concepts of modeling these problems, including recourse actions and the nonanticipativity principle. The book also includes the theory of two-stage and multistage stochastic programming problems; the current state of the theory on chance (probabilistic) constraints, including the structure of the problems, optimality theory, and duality; and statistical inference in and risk-averse approaches to stochastic programming.

Robust Discrete Optimization and Its Applications

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Publisher : Springer Science & Business Media
ISBN 13 : 1475726201
Total Pages : 373 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Robust Discrete Optimization and Its Applications by : Panos Kouvelis

Download or read book Robust Discrete Optimization and Its Applications written by Panos Kouvelis and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with decision making in environments of significant data un certainty, with particular emphasis on operations and production management applications. For such environments, we suggest the use of the robustness ap proach to decision making, which assumes inadequate knowledge of the decision maker about the random state of nature and develops a decision that hedges against the worst contingency that may arise. The main motivating factors for a decision maker to use the robustness approach are: • It does not ignore uncertainty and takes a proactive step in response to the fact that forecasted values of uncertain parameters will not occur in most environments; • It applies to decisions of unique, non-repetitive nature, which are common in many fast and dynamically changing environments; • It accounts for the risk averse nature of decision makers; and • It recognizes that even though decision environments are fraught with data uncertainties, decisions are evaluated ex post with the realized data. For all of the above reasons, robust decisions are dear to the heart of opera tional decision makers. This book takes a giant first step in presenting decision support tools and solution methods for generating robust decisions in a variety of interesting application environments. Robust Discrete Optimization is a comprehensive mathematical programming framework for robust decision making.