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Provides insights, scenarios, and applications to help students embrace uncertainty and become creative authors of their own futures.
In Uncertainty by Design Limor Samimian-Darash presents cases of the use of scenario technology in the fields of security and emergency preparedness, energy, and health by analyzing scenario narratives and practices at the National Emergency Management Authority in Israel, the World Health Organization's Regional Office for Europe, and the World Energy Council. Humankind has long struggled with the uncertainty of the future, with how to foresee the future, imagine alternatives, or prepare for and guard against undesirable eventualities. Scenario—or scenario planning—emerged in recent decades to become a widespread means through which states, large corporations, and local organizations imagine and prepare for the future. The scenario technology cases examined in Uncertainty by Design provide a useful lens through which to view contemporary efforts to engage in an overall journey of discovering the future, along with the modality of governing involved in these endeavors to face future uncertainties. Collectively, they enable us to understand in depth how scenarios express a new governing modality.
In Uncertainty by Design Limor Samimian-Darash presents cases of the use of scenario technology in the fields of security and emergency preparedness, energy, and health by analyzing scenario narratives and practices at the National Emergency Management Authority in Israel, the World Health Organization's Regional Office for Europe, and the World Energy Council. Humankind has long struggled with the uncertainty of the future, with how to foresee the future, imagine alternatives, or prepare for and guard against undesirable eventualities. Scenario—or scenario planning—emerged in recent decades to become a widespread means through which states, large corporations, and local organizations imagine and prepare for the future. The scenario technology cases examined in Uncertainty by Design provide a useful lens through which to view contemporary efforts to engage in an overall journey of discovering the future, along with the modality of governing involved in these endeavors to face future uncertainties. Collectively, they enable us to understand in depth how scenarios express a new governing modality.
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 methodology to model uncertainty and make choices when we have limited information. This methodology must use all available information and rely only on assumptions that are supported by evidence. This book explains theories and tools to represent uncertainty using both data and expert judgment. It teaches the reader how to make design or business decisions when there is limited information with these tools. Readers will learn a structured, risk-based approach, which is based on common sense principles, for design and business decisions. These decisions are consistent with the decision-maker¿s risk attitude. The book is exceptionally suited as educational material because it uses everyday language and real-life examples to elucidate concepts. It demonstrates how these concepts touch our lives through many practical examples, questions and exercises. These are designed to help students learn that first they should understand a problem and then establish a strategy for solving it, instead of using trial-and-error approaches. This volume is intended for undergraduate and graduate courses in mechanical, civil, industrial, aerospace, and ocean engineering and for researchers and professionals in these disciplines. It will also benefit managers and students in business administration who want to make good decisions with limited information.
How uncertainty in games -- from Super Mario Bros. to Rock/Paper/Scissors -- engages players and shapes play experiences.
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
In the realm of engineering structures design, the inevitability of uncertainties poses a significant challenge. Uncertainty-Based Multidisciplinary Design and Optimization (UBMDO) stands out for its dual ability to precisely quantify the impact of uncertain variables and harness the potential of multidisciplinary design and optimization, thereby attracting considerable attention. From basic theory to advanced applications, this book helps readers achieve more efficient and reliable design optimization in complex systems through rich case studies and practical technical guidance. The book systematically expounds the fundamental theories and methods of UBMDO, encompassing crucial techniques such as uncertainty modeling, sensitivity analysis, approximate modeling, and uncertainty-based optimization. It also introduces various uncertainty analysis methods, such as stochastic, non-probabilistic, and hybrid approaches, aiding readers in comprehending and managing uncertainty within systems. Through diverse practical engineering cases in fields like machinery, aerospace, and energy, it illustrates the specific application and implementation process of the UBMDO method. Rich graphics, algorithms, and simulation results augment the practicality and applicability of the theoretical knowledge. Furthermore, it explores in depth the future development trends and challenges of UBMDO, sparking innovative thinking and research interests among readers in this field. Multidisciplinary Design Optimization of Complex Structures Under Uncertainty caters to a diverse audience: Engineers specializing in multidisciplinary design optimization are given the tools to master uncertainty management, and researchers in related fields will gain important theoretical insights and practical guidance in uncertainty analysis. Additionally, scholars and educators can utilize the book as a comprehensive resource for advanced courses, enabling students to grasp the latest UBMDO applications. Decision makers and managers handling complex systems can extract methods from the book, facilitating improved risk assessment, and strategic development through uncertainty-based optimization.
This book is a rigorous but practical presentation of the techniques of uncertainty quantification, with applications in R and Python. This volume includes mathematical arguments at the level necessary to make the presentation rigorous and the assumptions clearly established, while maintaining a focus on practical applications of uncertainty quantification methods. Practical aspects of applied probability are also discussed, making the content accessible to students. The introduction of R and Python allows the reader to solve more complex problems involving a more significant number of variables. Users will be able to use examples laid out in the text to solve medium-sized problems. The list of topics covered in this volume includes linear and nonlinear programming, Lagrange multipliers (for sensitivity), multi-objective optimization, game theory, as well as linear algebraic equations, and probability and statistics. Blending theoretical rigor and practical applications, this volume will be of interest to professionals, researchers, graduate and undergraduate students interested in the use of uncertainty quantification techniques within the framework of operations research and mathematical programming, for applications in management and planning.
The 2020 International Conference on Uncertainty Quantification & Optimization gathered together internationally renowned researchers in the fields of optimization and uncertainty quantification. The resulting proceedings cover all related aspects of computational uncertainty management and optimization, with particular emphasis on aerospace engineering problems. The book contributions are organized under four major themes: Applications of Uncertainty in Aerospace & Engineering Imprecise Probability, Theory and Applications Robust and Reliability-Based Design Optimisation in Aerospace Engineering Uncertainty Quantification, Identification and Calibration in Aerospace Models This proceedings volume is useful across disciplines, as it brings the expertise of theoretical and application researchers together in a unified framework.