Robust Modeling And Planning
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| Author | : Kim, Dookie |
| Publisher | : IGI Global |
| Total Pages | : 644 |
| Release | : 2018-06-15 |
| Genre | : Technology & Engineering |
| ISBN | : 1522547673 |
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.
| Author | : Aharon Ben-Tal |
| Publisher | : Princeton University Press |
| Total Pages | : 565 |
| Release | : 2009-08-10 |
| Genre | : Mathematics |
| ISBN | : 1400831059 |
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.
| Author | : Jocelyn Sabatier |
| Publisher | : Springer |
| Total Pages | : 330 |
| Release | : 2015-05-06 |
| Genre | : Technology & Engineering |
| ISBN | : 9401798079 |
This book provides an overview of the research done and results obtained during the last ten years in the fields of fractional systems control, fractional PI and PID control, robust and CRONE control, and fractional path planning and path tracking. Coverage features theoretical results, applications and exercises. The book will be useful for post-graduate students who are looking to learn more on fractional systems and control. In addition, it will also appeal to researchers from other fields interested in increasing their knowledge in this area.
| Author | : Christine H. Mueller |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 246 |
| Release | : 2012-12-06 |
| Genre | : Mathematics |
| ISBN | : 1461222966 |
Robust statistics and the design of experiments are two of the fastest growing fields in contemporary statistics. Up to now, there has been very little overlap between these fields. This is the first book to link these two areas by studying the influence of the design on the efficiency and robustness of robust estimators and tests. The classical approaches of experimental design and robust statistics are introduced before the areas are linked, and the author shows that robust statistical procedures profit by an appropriate choice of the design and that efficient designs for a robust statistical analysis are more applicable.
| Author | : Sung H. Park |
| Publisher | : World Scientific |
| Total Pages | : 558 |
| Release | : 2008 |
| Genre | : Technology & Engineering |
| ISBN | : 9812778675 |
This book is written primarily for engineers and researchers who use statistical robust design for quality engineering and Six Sigma, and for statisticians who wish to know about the wide range of applications of experimental design in industry. It is a valuable guide and reference material for students, managers, quality improvement specialists and other professionals interested in Taguchi's robust design methods as well as the implementation of Six Sigma. This book can also be useful to those who would like to learn about the role of Robust Design within the Six Sigma (Improve phase) methodology and Design for Six Sigma (DFSS) (Optimize) methodology. It combines classical experimental design methods with those of Taguchi's robust designs, demonstrating their prowess in DFSS and suggesting new directions for the development of statistical design and analysis.
| Author | : David Nicholls |
| Publisher | : RIAC |
| Total Pages | : 462 |
| Release | : 2011-06 |
| Genre | : Technology & Engineering |
| ISBN | : 1933904356 |
Historically, the reliability growth process has been thought of, and treated as, a reactive approach to growing reliability based on failures "discovered" during testing or, most unfortunately, once a system/product has been delivered to a customer. As a result, many reliability growth models are predicated on starting the reliability growth process at test time "zero", with some initial level of reliability (usually in the context of a time-based measure such as Mean Time Between Failure (MTBF)). Time "zero" represents the start of testing, and the initial reliability of the test item is based on its inherent design. The problem with this approach, still predominant today, is that it ignores opportunities to grow reliability during the design of a system or product, i.e., opportunities to go into reliability growth testing with a higher initial inherent reliability at time zero. In addition to the traditional approaches to reliability growth during test, this book explores the activities and opportunities that can be leveraged to promote and achieve reliability growth during the design phase of the overall system life cycle. The ability to do so as part of an integrated, proactive design environment has significant implications for developing and delivering reliable items quickly, on time and within budget. This book offers new definitions of how failures can be characterized, and how those new definitions can be used to develop metrics that will quantify how effective a Design for Reliability (DFR) process is in (1) identifying failure modes and (2) mitigating their root failure causes. Reliability growth can only occur in the presence of both elements.
| Author | : Giuseppe Calafiore |
| Publisher | : Springer |
| Total Pages | : 0 |
| Release | : 2012-03-14 |
| Genre | : Technology & Engineering |
| ISBN | : 9781849965521 |
Probabilistic and Randomized Methods for Design under Uncertainty is a collection of contributions from the world’s leading experts in a fast-emerging branch of control engineering and operations research. The book will be bought by university researchers and lecturers along with graduate students in control engineering and operational research.
| Author | : Xu Andy Sun |
| Publisher | : Springer Nature |
| Total Pages | : 337 |
| Release | : 2021-11-08 |
| Genre | : Business & Economics |
| ISBN | : 3030851281 |
This book covers robust optimization theory and applications in the electricity sector. The advantage of robust optimization with respect to other methodologies for decision making under uncertainty are first discussed. Then, the robust optimization theory is covered in a friendly and tutorial manner. Finally, a number of insightful short- and long-term applications pertaining to the electricity sector are considered. Specifically, the book includes: robust set characterization, robust optimization, adaptive robust optimization, hybrid robust-stochastic optimization, applications to short- and medium-term operations problems in the electricity sector, and applications to long-term investment problems in the electricity sector. Each chapter contains end-of-chapter problems, making it suitable for use as a text. The purpose of the book is to provide a self-contained overview of robust optimization techniques for decision making under uncertainty in the electricity sector. The targeted audience includes industrial and power engineering students and practitioners in energy fields. The young field of robust optimization is reaching maturity in many respects. It is also useful for practitioners, as it provides a number of electricity industry applications described up to working algorithms (in JuliaOpt).
| Author | : Vincent A. W. J. Marchau |
| Publisher | : Springer |
| Total Pages | : 408 |
| Release | : 2019-04-04 |
| Genre | : Business & Economics |
| ISBN | : 3030052524 |
This open access book focuses on both the theory and practice associated with the tools and approaches for decisionmaking in the face of deep uncertainty. It explores approaches and tools supporting the design of strategic plans under deep uncertainty, and their testing in the real world, including barriers and enablers for their use in practice. The book broadens traditional approaches and tools to include the analysis of actors and networks related to the problem at hand. It also shows how lessons learned in the application process can be used to improve the approaches and tools used in the design process. The book offers guidance in identifying and applying appropriate approaches and tools to design plans, as well as advice on implementing these plans in the real world. For decisionmakers and practitioners, the book includes realistic examples and practical guidelines that should help them understand what decisionmaking under deep uncertainty is and how it may be of assistance to them. Decision Making under Deep Uncertainty: From Theory to Practice is divided into four parts. Part I presents five approaches for designing strategic plans under deep uncertainty: Robust Decision Making, Dynamic Adaptive Planning, Dynamic Adaptive Policy Pathways, Info-Gap Decision Theory, and Engineering Options Analysis. Each approach is worked out in terms of its theoretical foundations, methodological steps to follow when using the approach, latest methodological insights, and challenges for improvement. In Part II, applications of each of these approaches are presented. Based on recent case studies, the practical implications of applying each approach are discussed in depth. Part III focuses on using the approaches and tools in real-world contexts, based on insights from real-world cases. Part IV contains conclusions and a synthesis of the lessons that can be drawn for designing, applying, and implementing strategic plans under deep uncertainty, as well as recommendations for future work. The publication of this book has been funded by the Radboud University, the RAND Corporation, Delft University of Technology, and Deltares.
| Author | : Stephen Gorard |
| Publisher | : SAGE |
| Total Pages | : 234 |
| Release | : 2013-02-01 |
| Genre | : Social Science |
| ISBN | : 1446290859 |
Research design is of critical importance in social research, despite its relative neglect in many methods resources. Early consideration of design in relation to research questions leads to the elimination or diminution of threats to eventual research claims, by encouraging internal validity and substantially reducing the number of alternative explanations for any finite number of research ′observations′. This new book: discusses the nature of design; gives an introduction to design notation; offers a flexible approach to new designs; looks at a range of standard design models; and presents craft tips for real-life problems and compromises. Most importantly, it provides the rationale for preferring one design over another within any given context. Each section is illustrated with case studies of real work and concludes with suggested readings and topics for discussion in seminars and workshops, making it an ideal textbook for postgraduate research methods courses. Based on the author′s teaching on the ESRC Doctoral Training Centre "Masters in Research Methods" at the University of Birmingham, and his ongoing work for the ESRC Researcher Development Initiative, this is an essential text for postgraduate researchers and academics. There is no book like Research Design on the market that addresses all of these issues in an easy to comprehend style, for those who want to design research and make critical judgements about the designs of others.
