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Decision Based Design Under Uncertainty With Intervals
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Book Synopsis Decision-based Design Under Uncertainty with Intervals by : Sashank Vasireddy
Download or read book Decision-based Design Under Uncertainty with Intervals written by Sashank Vasireddy and published by . This book was released on 2009 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Design requires a series of decisions, and one of the major challenges engineering designers face is making decisions under uncertainty. The engineering designer must choose the best design among various alternatives. This work evaluates the use of utility functions to make decisions under uncertainty with both random and interval variables. Uncertainty cannot be eliminated completely, but it can be reduced. Most current methods treat only aleatory uncertainty. Here, however, both aleatory and epistemic uncertainties are addressed in the context of engineering design. Methods such as moment matching method and worst case analysis are used to incorporate uncertainty into design problems"--Abstract, leaf iii.
Book Synopsis Design Decisions under Uncertainty with Limited Information by : Efstratios Nikolaidis
Download or read book Design Decisions under Uncertainty with Limited Information written by Efstratios Nikolaidis and published by CRC Press. This book was released on 2011-02-18 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today's business environment involves design decisions with significant uncertainty. To succeed, decision-makers should replace deterministic methods with a risk-based approach that accounts for the decision maker‘s risk tolerance. In many problems, it is impractical to collect data because rare or one-time events are involved. Therefore, we need a
Book Synopsis Eliminating Design Alternatives Under Interval-based Uncertainty by : Steven Joseph Rekuc
Download or read book Eliminating Design Alternatives Under Interval-based Uncertainty written by Steven Joseph Rekuc and published by . This book was released on 2005 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Typically, design is approached as a sequence of decisions in which designers select what they believe to be the best alternative in each decision. While this approach can be used to arrive at a final solution quickly, it is unlikely to result in the most-preferred solution. The reason for this is that all the decisions in the design process are coupled. To determine the most preferred alternative in the current decision, the designer would need to know the outcomes of all future decisions, information that is currently unavailable or indeterminate. Since the designer cannot select a single alternative because of this indeterminate (interval-based) uncertainty, a set-based design approach is introduced. The approach is motivated by the engineering practices at Toyota and is based on the structure of the Branch and Bound Algorithm. Instead of selecting a single design alternative that is perceived as being the most preferred at the time of the decision, the proposed set-based design approach eliminates dominated design alternatives: rather than selecting the best, eliminate the worst. Starting from a large initial design space, the approach sequentially reduces the set of non-dominated design alternatives until no further reduction is possible - the remaining set cannot be rationally differentiated based on the available information. A single alternative is then selected from the remaining set of non-dominated designs. In this thesis, the focus is on the elimination step of the set-based design method: A criterion for rational elimination under interval-based uncertainty is derived. To be efficient, the criterion takes into account shared uncertainty - uncertainty shared between design alternatives. In taking this uncertainty into account, one is able to eliminate significantly more design alternatives, improving the efficiency of the set-based design approach. Additionally, the criterion uses a detailed reference design to allow more elimination of inferior design sets without evaluating each alternative in that set. The effectiveness of this elimination is demonstrated in two examples: a beam design and a gearbox design.
Book Synopsis Analysis and Design of Marine Structures V by : C. Guedes Soares
Download or read book Analysis and Design of Marine Structures V written by C. Guedes Soares and published by CRC Press. This book was released on 2015-03-11 with total page 814 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analysis and Design of Marine Structures V contains the papers presented at MARSTRUCT 2015, the 5th International Conference on Marine Structures (Southampton, UK, 25-27 March 2015). The MARSTRUCT series of conferences started in Glasgow, UK in 2007, the second event of the series took place in Lisbon, Portugal (2009), while the third was in Hambur
Book Synopsis Decision Based Design by : Vijitashwa Pandey
Download or read book Decision Based Design written by Vijitashwa Pandey and published by CRC Press. This book was released on 2013-08-20 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a presentation that formalizes what makes up decision based design, Decision Based Design defines the major concepts that go into product realization. It presents all major concepts in design decision making in an integrated way and covers the fundamentals of decision analysis in engineering design. It also trains engineers to understand the imp
Book Synopsis What Every Engineer Should Know About Decision Making Under Uncertainty by : John X. Wang
Download or read book What Every Engineer Should Know About Decision Making Under Uncertainty written by John X. Wang and published by CRC Press. This book was released on 2002-07-01 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covering the prediction of outcomes for engineering decisions through regression analysis, this succinct and practical reference presents statistical reasoning and interpretational techniques to aid in the decision making process when faced with engineering problems. The author emphasizes the use of spreadsheet simulations and decision trees as imp
Book Synopsis Decisions under Uncertainty by : Ian Jordaan
Download or read book Decisions under Uncertainty written by Ian Jordaan and published by Cambridge University Press. This book was released on 2005-04-07 with total page 690 pages. Available in PDF, EPUB and Kindle. Book excerpt: To better understand the core concepts of probability and to see how they affect real-world decisions about design and system performance, engineers and scientists might want to ask themselves the following questions: what exactly is meant by probability? What is the precise definition of the 100-year load and how is it calculated? What is an 'extremal' probability distribution? What is the Bayesian approach? How is utility defined? How do games fit into probability theory? What is entropy? How do I apply these ideas in risk analysis? Starting from the most basic assumptions, this 2005 book develops a coherent theory of probability and broadens it into applications in decision theory, design, and risk analysis. This book is written for engineers and scientists interested in probability and risk. It can be used by undergraduates, graduate students, or practicing engineers.
Book Synopsis Decision Making Under Uncertainty by : Mykel J. Kochenderfer
Download or read book Decision Making Under Uncertainty written by Mykel J. Kochenderfer and published by MIT Press. This book was released on 2015-07-24 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.
Book Synopsis Marine Design XIII, Volume 1 by : Pentti Kujala
Download or read book Marine Design XIII, Volume 1 written by Pentti Kujala and published by CRC Press. This book was released on 2018-06-04 with total page 1077 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is volume 1 of a 2-volume set. Marine Design XIII collects the contributions to the 13th International Marine Design Conference (IMDC 2018, Espoo, Finland, 10-14 June 2018). The aim of this IMDC series of conferences is to promote all aspects of marine design as an engineering discipline. The focus is on key design challenges and opportunities in the area of current maritime technologies and markets, with special emphasis on: • Challenges in merging ship design and marine applications of experience-based industrial design • Digitalisation as technological enabler for stronger link between efficient design, operations and maintenance in future • Emerging technologies and their impact on future designs • Cruise ship and icebreaker designs including fleet compositions to meet new market demands To reflect on the conference focus, Marine Design XIII covers the following research topic series: •State of art ship design principles - education, design methodology, structural design, hydrodynamic design; •Cutting edge ship designs and operations - ship concept design, risk and safety, arctic design, autonomous ships; •Energy efficiency and propulsions - energy efficiency, hull form design, propulsion equipment design; •Wider marine designs and practices - navy ships, offshore and wind farms and production. Marine Design XIII contains 2 state-of-the-art reports on design methodologies and cruise ships design, and 4 keynote papers on new directions for vessel design practices and tools, digital maritime traffic, naval ship designs, and new tanker design for arctic. Marine Design XIII will be of interest to academics and professionals in maritime technologies and marine design.
Book Synopsis Probabilistic and Randomized Methods for Design under Uncertainty by : Giuseppe Calafiore
Download or read book Probabilistic and Randomized Methods for Design under Uncertainty written by Giuseppe Calafiore and published by Springer Science & Business Media. This book was released on 2006-03-06 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach by : Bilal Ayyub
Download or read book Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach written by Bilal Ayyub and published by Springer Science & Business Media. This book was released on 1997-10-31 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty has been of concern to engineers, managers and . scientists for many centuries. In management sciences there have existed definitions of uncertainty in a rather narrow sense since the beginning of this century. In engineering and uncertainty has for a long time been considered as in sciences, however, synonymous with random, stochastic, statistic, or probabilistic. Only since the early sixties views on uncertainty have ~ecome more heterogeneous and more tools to model uncertainty than statistics have been proposed by several scientists. The problem of modeling uncertainty adequately has become more important the more complex systems have become, the faster the scientific and engineering world develops, and the more important, but also more difficult, forecasting of future states of systems have become. The first question one should probably ask is whether uncertainty is a phenomenon, a feature of real world systems, a state of mind or a label for a situation in which a human being wants to make statements about phenomena, i. e. , reality, models, and theories, respectively. One cart also ask whether uncertainty is an objective fact or just a subjective impression which is closely related to individual persons. Whether uncertainty is an objective feature of physical real systems seems to be a philosophical question. This shall not be answered in this volume.
Book Synopsis Decision Making Under Interval Uncertainty by : Vladik Kreinovich
Download or read book Decision Making Under Interval Uncertainty written by Vladik Kreinovich and published by . This book was released on 2015-01-31 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Fuzzy Preference Ordering of Interval Numbers in Decision Problems by : Atanu Sengupta
Download or read book Fuzzy Preference Ordering of Interval Numbers in Decision Problems written by Atanu Sengupta and published by Springer. This book was released on 2009-02-24 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: In conventional mathematical programming, coefficients of problems are usually determined by the experts as crisp values in terms of classical mathematical reasoning. But in reality, in an imprecise and uncertain environment, it will be utmost unrealistic to assume that the knowledge and representation of an expert can come in a precise way. The wider objective of the book is to study different real decision situations where problems are defined in inexact environment. Inexactness are mainly generated in two ways – (1) due to imprecise perception and knowledge of the human expert followed by vague representation of knowledge as a DM; (2) due to huge-ness and complexity of relations and data structure in the definition of the problem situation. We use interval numbers to specify inexact or imprecise or uncertain data. Consequently, the study of a decision problem requires answering the following initial questions: How should we compare and define preference ordering between two intervals?, interpret and deal inequality relations involving interval coefficients?, interpret and make way towards the goal of the decision problem? The present research work consists of two closely related fields: approaches towards defining a generalized preference ordering scheme for interval attributes and approaches to deal with some issues having application potential in many areas of decision making.
Book Synopsis Design Optimization Under Uncertainty by : Weifei Hu
Download or read book Design Optimization Under Uncertainty written by Weifei Hu and published by Springer Nature. This book was released on 2023-12-22 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the fundamentals of probability, statistical, and reliability concepts, the classical methods of uncertainty quantification and analytical reliability analysis, and the state-of-the-art approaches of design optimization under uncertainty (e.g., reliability-based design optimization and robust design optimization). The topics include basic concepts of probability and distributions, uncertainty quantification using probabilistic methods, classical reliability analysis methods, time-variant reliability analysis methods, fundamentals of deterministic design optimization, reliability-based design optimization, robust design optimization, other methods of design optimization under uncertainty, and engineering applications of design optimization under uncertainty.
Download or read book Decision-Based Design written by Wei Chen and published by Springer Science & Business Media. This book was released on 2012-08-22 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Building upon the fundamental principles of decision theory, Decision-Based Design: Integrating Consumer Preferences into Engineering Design presents an analytical approach to enterprise-driven Decision-Based Design (DBD) as a rigorous framework for decision making in engineering design. Once the related fundamentals of decision theory, economic analysis, and econometrics modelling are established, the remaining chapters describe the entire process, the associated analytical techniques, and the design case studies for integrating consumer preference modeling into the enterprise-driven DBD framework. Methods for identifying key attributes, optimal design of human appraisal experiments, data collection, data analysis, and demand model estimation are presented and illustrated using engineering design case studies. The scope of the chapters also provides: A rigorous framework of integrating the interests from both producer and consumers in engineering design, Analytical techniques of consumer choice modelling to forecast the impact of engineering decisions, Methods for synthesizing business and engineering models in multidisciplinary design environments, and Examples of effective application of Decision-Based Design supported by case studies. No matter whether you are an engineer facing decisions in consumer related product design, an instructor or student of engineering design, or a researcher exploring the role of decision making and consumer choice modelling in design, Decision-Based Design: Integrating Consumer Preferences into Engineering Design provides a reliable reference over a range of key topics.
Book Synopsis Bounded Rationality in Decision Making Under Uncertainty: Towards Optimal Granularity by : Joe Lorkowski
Download or read book Bounded Rationality in Decision Making Under Uncertainty: Towards Optimal Granularity written by Joe Lorkowski and published by Springer. This book was released on 2017-07-01 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses an intriguing question: are our decisions rational? It explains seemingly irrational human decision-making behavior by taking into account our limited ability to process information. It also shows with several examples that optimization under granularity restriction leads to observed human decision-making. Drawing on the Nobel-prize-winning studies by Kahneman and Tversky, researchers have found many examples of seemingly irrational decisions: e.g., we overestimate the probability of rare events. Our explanation is that since human abilities to process information are limited, we operate not with the exact values of relevant quantities, but with “granules” that contain these values. We show that optimization under such granularity indeed leads to observed human behavior. In particular, for the first time, we explain the mysterious empirical dependence of betting odds on actual probabilities. This book can be recommended to all students interested in human decision-making, to researchers whose work involves human decisions, and to practitioners who design and employ systems involving human decision-making —so that they can better utilize our ability to make decisions under uncertainty.
Book Synopsis Decision Making under Deep Uncertainty by : Vincent A. W. J. Marchau
Download or read book Decision Making under Deep Uncertainty written by Vincent A. W. J. Marchau and published by Springer. This book was released on 2019-04-04 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
