Robust Optimization
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Robust Optimization
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Author : Aharon Ben-Tal
language : en
Publisher: Princeton University Press
Release Date : 2009-08-10
Robust Optimization written by Aharon Ben-Tal and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-08-10 with Mathematics categories.
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.
Robust Discrete Optimization And Its Applications
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Author : Panos Kouvelis
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Robust Discrete Optimization And Its Applications written by Panos Kouvelis and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Mathematics categories.
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.
Robust Optimization
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Author : Subir Chowdhury
language : en
Publisher: John Wiley & Sons
Release Date : 2016-01-20
Robust Optimization written by Subir Chowdhury and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-20 with Technology & Engineering categories.
Robust Optimization is a method to improve robustness using low-cost variations of a single, conceptual design. The benefits of Robust Optimization include faster product development cycles; faster launch cycles; fewer manufacturing problems; fewer field problems; lower-cost, higher performing products and processes; and lower warranty costs. All these benefits can be realized if engineering and product development leadership of automotive and manufacturing organizations leverage the power of using Robust Optimization as a competitive weapon. Written by world renowned authors, Robust Optimization: World’s Best Practices for Developing Winning Vehicles, is a ground breaking book whichintroduces the technical management strategy of Robust Optimization. The authors discuss what the strategy entails, 8 steps for Robust Optimization and Robust Assessment, and how to lead it in a technical organization with an implementation strategy. Robust Optimization is defined and it is demonstrated how the techniques can be applied to manufacturing organizations, especially those with automotive industry applications, so that Robust Optimization creates the flexibility that minimizes product development cost, reduces product time-to-market, and increases overall productivity. Key features: Presents best practices from around the globe on Robust Optimization that can be applied in any manufacturing and automotive organization in the world Includes 19 successfully implemented best case studies from automotive original equipment manufacturers and suppliers Provides manufacturing industries with proven techniques to become more competitive in the global market Provides clarity concerning the common misinterpretations on Robust Optimization Robust Optimization: World’s Best Practices for Developing Winning Vehicles is a must-have book for engineers and managers who are working on design, product, manufacturing, mechanical, electrical, process, quality area; all levels of management especially in product development area, research and development personnel and consultants. It also serves as an excellent reference for students and teachers in engineering.
Robust Optimization Of Spline Models And Complex Regulatory Networks
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Author : Ayşe Özmen
language : en
Publisher: Springer
Release Date : 2016-05-11
Robust Optimization Of Spline Models And Complex Regulatory Networks written by Ayşe Özmen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-11 with Business & Economics categories.
This book introduces methods of robust optimization in multivariate adaptive regression splines (MARS) and Conic MARS in order to handle uncertainty and non-linearity. The proposed techniques are implemented and explained in two-model regulatory systems that can be found in the financial sector and in the contexts of banking, environmental protection, system biology and medicine. The book provides necessary background information on multi-model regulatory networks, optimization and regression. It presents the theory of and approaches to robust (conic) multivariate adaptive regression splines - R(C)MARS – and robust (conic) generalized partial linear models – R(C)GPLM – under polyhedral uncertainty. Further, it introduces spline regression models for multi-model regulatory networks and interprets (C)MARS results based on different datasets for the implementation. It explains robust optimization in these models in terms of both the theory and methodology. In this context it studies R(C)MARS results with different uncertainty scenarios for a numerical example. Lastly, the book demonstrates the implementation of the method in a number of applications from the financial, energy, and environmental sectors, and provides an outlook on future research.
Active Robust Optimization Optimizing For Robustness Of Changeable Products
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Author : Shaul Salomon
language : en
Publisher: Springer
Release Date : 2019-07-06
Active Robust Optimization Optimizing For Robustness Of Changeable Products written by Shaul Salomon and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-06 with Technology & Engineering categories.
This book presents a novel framework, known as Active Robust Optimization, which provides the tools for evaluating, comparing and optimizing changeable products. Since any product that can change its configuration during normal operation may be considered a “changeable product,” the framework is widely applicable. Further, the methodology enables designers to use adaptability to deal with uncertainties and so avoid over-conservative designs. Offering a comprehensive overview of the framework, including its unique features, such as its ability to optimally respond to uncertain situations, the book also defines a new class of optimization problem and examines the effects of changes in various parameters on their solution. Lastly, it discusses innovative approaches for solving the problem and demonstrates these with two examples from different fields in engineering design: optimization of an optical table and optimization of a gearbox.
Robustness Analysis In Decision Aiding Optimization And Analytics
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Author : Michael Doumpos
language : en
Publisher: Springer
Release Date : 2016-07-12
Robustness Analysis In Decision Aiding Optimization And Analytics written by Michael Doumpos and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-12 with Business & Economics categories.
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.
Optimization Methods In Finance
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Author : Gerard Cornuejols
language : en
Publisher: Cambridge University Press
Release Date : 2006-12-21
Optimization Methods In Finance written by Gerard Cornuejols and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-12-21 with Mathematics categories.
Optimization models play an increasingly important role in financial decisions. This is the first textbook devoted to explaining how recent advances in optimization models, methods and software can be applied to solve problems in computational finance more efficiently and accurately. Chapters discussing the theory and efficient solution methods for all major classes of optimization problems alternate with chapters illustrating their use in modeling problems of mathematical finance. The reader is guided through topics such as volatility estimation, portfolio optimization problems and constructing an index fund, using techniques such as nonlinear optimization models, quadratic programming formulations and integer programming models respectively. The book is based on Master's courses in financial engineering and comes with worked examples, exercises and case studies. It will be welcomed by applied mathematicians, operational researchers and others who work in mathematical and computational finance and who are seeking a text for self-learning or for use with courses.
Robust Optimal Planning And Operation Of Electrical Energy Systems
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Author : Behnam Mohammadi-ivatloo
language : en
Publisher: Springer
Release Date : 2019-02-06
Robust Optimal Planning And Operation Of Electrical Energy Systems written by Behnam Mohammadi-ivatloo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-06 with Technology & Engineering categories.
This book discusses the recent developments in robust optimization (RO) and information gap design theory (IGDT) methods and their application for the optimal planning and operation of electric energy systems. Chapters cover both theoretical background and applications to address common uncertainty factors such as load variation, power market price, and power generation of renewable energy sources. Case studies with real-world applications are included to help undergraduate and graduate students, researchers and engineers solve robust power and energy optimization problems and provide effective and promising solutions for the robust planning and operation of electric energy systems.
Robustness Optimization For Iot Topology
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Author : Tie Qiu
language : en
Publisher: Springer Nature
Release Date : 2022-06-11
Robustness Optimization For Iot Topology written by Tie Qiu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-11 with Computers categories.
The IoT topology defines the way various components communicate with each other within a network. Topologies can vary greatly in terms of security, power consumption, cost, and complexity. Optimizing the IoT topology for different applications and requirements can help to boost the network’s performance and save costs. More importantly, optimizing the topology robustness can ensure security and prevent network failure at the foundation level. In this context, this book examines the optimization schemes for topology robustness in the IoT, helping readers to construct a robustness optimization framework, from self-organizing to intelligent networking. The book provides the relevant theoretical framework and the latest empirical research on robustness optimization of IoT topology. Starting with the self-organization of networks, it gradually moves to genetic evolution. It also discusses the application of neural networks and reinforcement learning to endow the node with self-learning ability to allow intelligent networking. This book is intended for students, practitioners, industry professionals, and researchers who are eager to comprehend the vulnerabilities of IoT topology. It helps them to master the research framework for IoT topology robustness optimization and to build more efficient and reliable IoT topologies in their industry.