Download or read book Chance Constrained Linear Programming with Distribution Free Constraints written by Frederick Marsden Allen and published by . This book was released on 1971 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: The report is concerned with methods of approximating the chance- constrained set S = (x such that/Pr(A x=or

Download or read book Distribution Free Methods for the Chance Constrained Programming Model written by Jon R. Thomas and published by . This book was released on 1972 with total page 57 pages. Available in PDF, EPUB and Kindle. Book excerpt: The paper is concerned with the development of certainty or deterministic equivalent nonlinear programming models from chance-constrained programming models. It contains a review of some of the historical developments in this area which were made by Charnes and Cooper, Kataoka, Miller and Wagner, Hillier, and Sengupta. The paper introduces a new, distribution free approach to chance-constrained programming which can be used with both single and joint chance constraints. Finally, the distribution free chance-constraned model is applied to the economic problem of input-output analysis.

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.

Download or read book Distribution free Uniformly tighter Linear Approximations for Chance constrained Programming written by Gabriel R. Bitran and published by . This book was released on 1990 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Distribution Free Methods for the Chance constrained Programming Model written by Jon R. Thomas (CAPT, USAF.) and published by . This book was released on 1972 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Systems and Management Science by Extremal Methods written by Fred Young Phillips and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume, Systems and Management Science by Extremal Methods, is the second in a series dedicated to honoring and extending the work of Abraham Charnes. The first volume, entitled Extremal Methods and Systems Analysis (Springer Verlag, Berlin, 1980), was edited by A.V. Fiacco and K.O. Kortanek. Subtitled "An International Symposium on the Occasion of Abraham Charnes' Sixtieth Birthday," this first volume consisted of a selection from papers presented at a conference in honor of Professor Charnes held at The University of Texas at Austin in September 1977. This second volume consists of papers, to be described more fully below, that were presented in a similar 2 conference held at the IC Institute of The University of Texas at Austin, Texas, in October of 1987, to honor Dr. Charnes on his seventieth birthday. All these papers were written by scholars and scientists whose own work has been affected by the contributions of this distinguished scholar and educator over a long period of time.

Download or read book Chaos Complexity and Leadership 2016 written by Şefika Şule Erçetin and published by Springer. This book was released on 2018-03-21 with total page 751 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the proceedings from the 2016 International Symposium on Chaos, Complexity and Leadership, and reflects current research results of chaos and complexity studies and their applications in various fields. Included are research papers in the fields of applied nonlinear methods, modeling of data and simulations, as well as theoretical achievements of chaos and complex systems. Also discussed are leadership and management applications of chaos and complexity theory.

Download or read book Stochastic Linear Programming written by Peter Kall and published by Springer Science & Business Media. This book was released on 2010-11-02 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edition of Stochastic Linear Programming: Models, Theory and Computation has been brought completely up to date, either dealing with or at least referring to new material on models and methods, including DEA with stochastic outputs modeled via constraints on special risk functions (generalizing chance constraints, ICC’s and CVaR constraints), material on Sharpe-ratio, and Asset Liability Management models involving CVaR in a multi-stage setup. To facilitate use as a text, exercises are included throughout the book, and web access is provided to a student version of the authors’ SLP-IOR software. Additionally, the authors have updated the Guide to Available Software, and they have included newer algorithms and modeling systems for SLP. The book is thus suitable as a text for advanced courses in stochastic optimization, and as a reference to the field. From Reviews of the First Edition: "The book presents a comprehensive study of stochastic linear optimization problems and their applications. ... The presentation includes geometric interpretation, linear programming duality, and the simplex method in its primal and dual forms. ... The authors have made an effort to collect ... the most useful recent ideas and algorithms in this area. ... A guide to the existing software is included as well." (Darinka Dentcheva, Mathematical Reviews, Issue 2006 c) "This is a graduate text in optimisation whose main emphasis is in stochastic programming. The book is clearly written. ... This is a good book for providing mathematicians, economists and engineers with an almost complete start up information for working in the field. I heartily welcome its publication. ... It is evident that this book will constitute an obligatory reference source for the specialists of the field." (Carlos Narciso Bouza Herrera, Zentralblatt MATH, Vol. 1104 (6), 2007)

Download or read book The Chance Constrained Critical Path for a Large Class of Distributions written by Abraham Charnes and published by . This book was released on 1988 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: M. Kress proved fpr a special class of Location-Scale probability distributions there always exists a probability level for which the Chance Constrained Critical Path (CCCP) remains unchanged for all probabilities greater than or equal to that value. His chance constrained problem has zero-order decision rules and individual chance constraints. This paper extends his results to most of the common probability distributions. Keywords: Chance constrained programming. (KR).

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.

Download or read book Probability and Algorithms written by National Research Council and published by National Academies Press. This book was released on 1992-02-01 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: Some of the hardest computational problems have been successfully attacked through the use of probabilistic algorithms, which have an element of randomness to them. Concepts from the field of probability are also increasingly useful in analyzing the performance of algorithms, broadening our understanding beyond that provided by the worst-case or average-case analyses. This book surveys both of these emerging areas on the interface of the mathematical sciences and computer science. It is designed to attract new researchers to this area and provide them with enough background to begin explorations of their own.

Download or read book In Productivity Finance and Operations written by Kenneth D. Lawrence and published by Emerald Group Publishing. This book was released on 2006-06-13 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Talks about the applications of management science to: Multi-Criteria Decision Making, Operations and Supply Chain Management, Productivity Management (DEA), and Financial Management. This book provides an overview of some of the most essential aspects of the discipline. It is suitable for persons interested in management or management science.

Download or read book In Productivity Finance and Operations written by Ronald K. Klimberg - USE 0048 and published by Emerald Group Publishing. This book was released on 2006-06-13 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Talks about the applications of management science to: Multi-Criteria Decision Making, Operations and Supply Chain Management, Productivity Management (DEA), and Financial Management. This book provides an overview of some of the most essential aspects of the discipline. It is suitable for persons interested in management or management science.

Download or read book Data Driven Distributionally Robust Chance Constrained Optimization With Wasserstein Metric written by Ran Ji and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We study distributionally robust chance-constrained programming (DRCCP) optimization problems with data-driven Wasserstein ambiguity sets. The proposed algorithmic and reformulation framework applies to distributionally robust optimization problems subjected to individual as well as joint chance constraints, with random right-hand side and technology vector, and under two types of uncertainties, called uncertain probabilities and continuum of realizations. For the uncertain probabilities case, we provide new mixed-integer linear programming reformulations for DRCCP problems and derive a set of precedence optimality cuts to strengthen the formulations. For the continuum of realizations case with random right-hand side, we propose an exact mixed-integer second-order cone programming (MISOCP) reformulation and a linear programming (LP) outer approximation. For the continuum of realizations case with random technology vector, we propose two MISOCP and LP outer approximations. We show that all proposed relaxations become exact reformulations when the decision variables are binary or bounded general integers. We evaluate the scalability and tightness of the proposed MISOCP and (MI)LP formulations on a distributionally robust chance constrained knapsack problem.

Download or read book Stochastic Linear Programming Algorithms written by Janos Mayer and published by Taylor & Francis. This book was released on 2022-04-19 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: A computationally oriented comparison of solution algorithms for two stage and jointly chance constrained stochastic linear programming problems, this is the first book to present comparative computational results with several major stochastic programming solution approaches. The following methods are considered: regularized decomposition, stochastic decomposition and successive discrete approximation methods for two stage problems; cutting plane methods, and a reduced gradient method for jointly chance constrained problems. The first part of the book introduces the algorithms, including a unified approach to decomposition methods and their regularized counterparts. The second part addresses computer implementation of the methods, describes a testing environment based on a model management system, and presents comparative computational results with the various algorithms. Emphasis is on the computational behavior of the algorithms.

Download or read book Lectures on Stochastic Programming Modeling and Theory Third Edition written by Alexander Shapiro and published by SIAM. This book was released on 2021-08-19 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible and rigorous presentation of contemporary models and ideas of stochastic programming, this book focuses on optimization problems involving uncertain parameters for which stochastic models are available. Since these problems occur in vast, diverse areas of science and engineering, there is much interest in rigorous ways of formulating, analyzing, and solving them. This substantially revised edition presents a modern theory of stochastic programming, including expanded and detailed coverage of sample complexity, risk measures, and distributionally robust optimization. It adds two new chapters that provide readers with a solid understanding of emerging topics; updates Chapter 6 to now include a detailed discussion of the interchangeability principle for risk measures; and presents new material on formulation and numerical approaches to solving periodical multistage stochastic programs. Lectures on Stochastic Programming: Modeling and Theory, Third Edition is written for researchers and graduate students working on theory and applications of optimization, with the hope that it will encourage them to apply stochastic programming models and undertake further studies of this fascinating and rapidly developing area.

Download or read book Robustness Analysis in Decision Aiding Optimization and Analytics written by Michael Doumpos and published by Springer. This book was released on 2016-07-12 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a broad coverage of the recent advances in robustness analysis in decision aiding, optimization, and analytics. It offers a comprehensive illustration of the challenges that robustness raises in different operations research and management science (OR/MS) contexts and the methodologies proposed from multiple perspectives. Aside from covering recent methodological developments, this volume also features applications of robust techniques in engineering and management, thus illustrating the robustness issues raised in real-world problems and their resolution within advances in OR/MS methodologies. Robustness analysis seeks to address issues by promoting solutions, which are acceptable under a wide set of hypotheses, assumptions and estimates. In OR/MS, robustness has been mostly viewed in the context of optimization under uncertainty. Several scholars, however, have emphasized the multiple facets of robustness analysis in a broader OR/MS perspective that goes beyond the traditional framework, seeking to cover the decision support nature of OR/MS methodologies as well. As new challenges emerge in a “big-data'” era, where the information volume, speed of flow, and complexity increase rapidly, and analytics play a fundamental role for strategic and operational decision-making at a global level, robustness issues such as the ones covered in this book become more relevant than ever for providing sound decision support through more powerful analytic tools.