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This book examines ongoing research and practice in using visualization to represent optimization models, explore optimum solutions, and summarize the results of the optimization effort. As research in optimization develops more powerful algorithms capable of analyzing ever more complicated problems, an increasing number of excellent books have been written to explain how to construct optimization models and how to build algorithms to analyze these models. However, solving problems using optimization techniques involves more than just developing newer, faster algorithms. Building, debugging, validating and understanding models and algorithms requires appropriate representations. This book describes how scientific visualization can enhance the representations needed for optimization. Although books on visualization exist, none of them have specifically addressed how visualization can contribute to optimization practice and research. In this book, relevant techniques of computer graphics, virtual reality, sonification, among others, are examined and specifically targeted to optimization. Moreover, applications of optimization to visualization are also explored.
This book highlights recent developments in multidimensional data visualization, presenting both new methods and modifications on classic techniques. Throughout the book, various applications of multidimensional data visualization are presented including its uses in social sciences (economy, education, politics, psychology), environmetrics, and medicine (ophthalmology, sport medicine, pharmacology, sleep medicine). The book provides recent research results in optimization-based visualization. Evolutionary algorithms and a two-level optimization method, based on combinatorial optimization and quadratic programming, are analyzed in detail. The performance of these algorithms and the development of parallel versions are discussed. The utilization of new visualization techniques to improve the capabilies of artificial neural networks (self-organizing maps, feed-forward networks) is also discussed. The book includes over 100 detailed images presenting examples of the many different visualization techniques that the book presents. This book is intended for scientists and researchers in any field of study where complex and multidimensional data must be represented visually.
Since the volume may be of interest to a broad variety of people, it is arranged in parts that require different levels of mathematical background. Part I can be assessed by those interested in the application of visualization methods in decision making. In Part II computational methods are introduced in a relatively simple form. Part III is written for readers in applied mathematics interested in the theoretical basis of modern optimization.
This book constitutes the refereed proceedings of the Second International Conference on Evolutionary Multi-Criterion Optimization, EMO 2003, held in Faro, Portugal, in April 2003. The 56 revised full papers presented were carefully reviewed and selected from a total of 100 submissions. The papers are organized in topical sections on objective handling and problem decomposition, algorithm improvements, online adaptation, problem construction, performance analysis and comparison, alternative methods, implementation, and applications.
Data visualization is currently a very active and vital area of research, teaching and development. The term unites the established field of scientific visualization and the more recent field of information visualization. The success of data visualization is due to the soundness of the basic idea behind it: the use of computer-generated images to gain insight and knowledge from data and its inherent patterns and relationships. A second premise is the utilization of the broad bandwidth of the human sensory system in steering and interpreting complex processes, and simulations involving data sets from diverse scientific disciplines and large collections of abstract data from many sources. These concepts are extremely important and have a profound and widespread impact on the methodology of computational science and engineering, as well as on management and administration. The interplay between various application areas and their specific problem solving visualization techniques is emphasized in this book. Reflecting the heterogeneous structure of Data Visualization, emphasis was placed on these topics: -Visualization Algorithms and Techniques; -Volume Visualization; -Information Visualization; -Multiresolution Techniques; -Interactive Data Exploration. Data Visualization: The State of the Art presents the state of the art in scientific and information visualization techniques by experts in this field. It can serve as an overview for the inquiring scientist, and as a basic foundation for developers. This edited volume contains chapters dedicated to surveys of specific topics, and a great deal of original work not previously published illustrated by examples from a wealth of applications. The book will also provide basic material for teaching the state of the art techniques in data visualization. Data Visualization: The State of the Art is designed to meet the needs of practitioners and researchers in scientific and information visualization. This book is also suitable as a secondary text for graduate level students in computer science and engineering.
Optimization is an important tool used in decision science and for the analysis of physical systems used in engineering. One can trace its roots to the Calculus of Variations and the work of Euler and Lagrange. This natural and reasonable approach to mathematical programming covers numerical methods for finite-dimensional optimization problems. It begins with very simple ideas progressing through more complicated concepts, concentrating on methods for both unconstrained and constrained optimization.
This book presents efficient visualization techniques, a prerequisite for the interactive exploration of complex data sets. High performance is demonstrated as a process of devising algorithms for the fast graphics processing units (GPUs) of modern graphics hardware. Coverage includes parallelization on cluster computers with several GPUs, adaptive rendering methods, and non-photorealistic rendering techniques for visualization.
Visualization and analysis tools, techniques, and algorithms have undergone a rapid evolution in recent decades to accommodate explosive growth in data size and complexity and to exploit emerging multi- and many-core computational platforms. High Performance Visualization: Enabling Extreme-Scale Scientific Insight focuses on the subset of scientifi
The realization of a successful product requires collaboration between developers and producers, taking account of stakeholder value, reinforcing the contribution of industry to society and enhancing the wellbeing of workers while respecting planetary boundaries. Founded in 2006, the Swedish Production Academy (SPA) aims to drive and develop production research and education and to increase cooperation within the production area. This book presents the proceedings of the 10th Swedish Production Symposium (SPS2022), held in Skövde, Sweden, from 26-29 April 2022. The overall theme of the symposium was ‘Industry 5.0 Transformation – Towards a Sustainable, Human-Centric, and Resilient Production’. Since its inception in 2007, the purpose of SPS has been to facilitate an event at which members and interested participants from industry and academia can meet to exchange ideas. The 69 papers accepted for presentation here are grouped into ten sections: resource-efficient production; flexible production; humans in the production system; circular production systems and maintenance; integrated product and production development; industrial optimization and decision-making; cyber-physical production systems and digital twins; innovative production processes and additive manufacturing; smart and resilient supply chains; and linking research and education. Also included are three sections covering the Special Sessions at SPS2022: artificial intelligence and industrial analytics in industry 4.0; development of resilient and sustainable production systems; and boundary crossing and boundary objects in product and production development. The book will be of interest to all those involved in the development and production of future products.
Convex optimization problems arise frequently in many different fields. This book provides a comprehensive introduction to the subject, and shows in detail how such problems can be solved numerically with great efficiency. The book begins with the basic elements of convex sets and functions, and then describes various classes of convex optimization problems. Duality and approximation techniques are then covered, as are statistical estimation techniques. Various geometrical problems are then presented, and there is detailed discussion of unconstrained and constrained minimization problems, and interior-point methods. The focus of the book is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. It contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance and economics.