Download or read book Large Scale and Distributed Optimization written by Pontus Giselsson and published by Springer. This book was released on 2018-11-11 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents tools and methods for large-scale and distributed optimization. Since many methods in "Big Data" fields rely on solving large-scale optimization problems, often in distributed fashion, this topic has over the last decade emerged to become very important. As well as specific coverage of this active research field, the book serves as a powerful source of information for practitioners as well as theoreticians. Large-Scale and Distributed Optimization is a unique combination of contributions from leading experts in the field, who were speakers at the LCCC Focus Period on Large-Scale and Distributed Optimization, held in Lund, 14th–16th June 2017. A source of information and innovative ideas for current and future research, this book will appeal to researchers, academics, and students who are interested in large-scale optimization.
Download or read book Distributed Optimization and Statistical Learning Via the Alternating Direction Method of Multipliers written by Stephen Boyd and published by Now Publishers Inc. This book was released on 2011 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: Surveys the theory and history of the alternating direction method of multipliers, and discusses its applications to a wide variety of statistical and machine learning problems of recent interest, including the lasso, sparse logistic regression, basis pursuit, covariance selection, support vector machines, and many others.
Download or read book Merging Optimization and Control in Power Systems written by Feng Liu and published by John Wiley & Sons. This book was released on 2022-08-23 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: Merging Optimization and Control in Power Systems A novel exploration of distributed control in power systems with insightful discussions of physical and cyber restrictions In Merging Optimization and Control in Power Systems an accomplished team of engineers deliver a comprehensive introduction to distributed optimal control in power systems. The book re-imagines control design within the framework of cyber-physical systems with restrictions in both the physical and cyber spaces, addressing operational constraints, non-smooth objective functions, rapid power fluctuations caused by renewable generations, partial control coverage, communication delays, and non-identical sampling rates. This book bridges the gap between optimization and control in two ways. First, optimization-based feedback control is explored. The authors describe feedback controllers which automatically drive system states asymptotically to specific, desired optimal working points. Second, the book discusses feedback-based optimization. Leveraging the philosophy of feedback control, the authors envision the online solving of complicated optimization and control problems of power systems to adapt to time-varying environments. Readers will also find: A thorough argument against the traditional and centralized hierarchy of power system control in favor of the merged approach described in the book Comprehensive explorations of the fundamental changes gripping the power system today, including the increasing penetration of renewable and distributed generation, the proliferation of electric vehicles, and increases in load demand Data, tables, illustrations, and case studies covering realistic power systems and experiments In-depth examinations of physical and cyber restrictions, as well as the robustness and adaptability of the proposed model Perfect for postgraduate students and researchers with the prerequisite knowledge of power system analysis, operation, and dynamics, convex optimization theory, and control theory, Merging Optimization and Control in Power Systems is an advanced and timely treatment of distributed optimal controller design.
Download or read book Distributed Optimization with Application to Power Systems and Control written by Engelmann, Alexander and published by KIT Scientific Publishing. This book was released on 2022-11-21 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical optimization techniques are among the most successful tools for controlling technical systems optimally with feasibility guarantees. Yet, they are often centralized—all data has to be collected in one central and computationally powerful entity. Methods from distributed optimization overcome this limitation. Classical approaches, however, are often not applicable due to non-convexities. This work develops one of the first frameworks for distributed non-convex optimization.
Download or read book Recent Advances in Model Predictive Control written by Timm Faulwasser and published by Springer Nature. This book was released on 2021-04-17 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on distributed and economic Model Predictive Control (MPC) with applications in different fields. MPC is one of the most successful advanced control methodologies due to the simplicity of the basic idea (measure the current state, predict and optimize the future behavior of the plant to determine an input signal, and repeat this procedure ad infinitum) and its capability to deal with constrained nonlinear multi-input multi-output systems. While the basic idea is simple, the rigorous analysis of the MPC closed loop can be quite involved. Here, distributed means that either the computation is distributed to meet real-time requirements for (very) large-scale systems or that distributed agents act autonomously while being coupled via the constraints and/or the control objective. In the latter case, communication is necessary to maintain feasibility or to recover system-wide optimal performance. The term economic refers to general control tasks and, thus, goes beyond the typically predominant control objective of set-point stabilization. Here, recently developed concepts like (strict) dissipativity of optimal control problems or turnpike properties play a crucial role. The book collects research and survey articles on recent ideas and it provides perspectives on current trends in nonlinear model predictive control. Indeed, the book is the outcome of a series of six workshops funded by the German Research Foundation (DFG) involving early-stage career scientists from different countries and from leading European industry stakeholders.
Download or read book Distributed Optimization and Learning written by Zhongguo Li and published by Elsevier. This book was released on 2024-07-18 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Distributed Optimization and Learning: A Control-Theoretic Perspective illustrates the underlying principles of distributed optimization and learning. The book presents a systematic and self-contained description of distributed optimization and learning algorithms from a control-theoretic perspective. It focuses on exploring control-theoretic approaches and how those approaches can be utilized to solve distributed optimization and learning problems over network-connected, multi-agent systems. As there are strong links between optimization and learning, this book provides a unified platform for understanding distributed optimization and learning algorithms for different purposes. - Provides a series of the latest results, including but not limited to, distributed cooperative and competitive optimization, machine learning, and optimal resource allocation - Presents the most recent advances in theory and applications of distributed optimization and machine learning, including insightful connections to traditional control techniques - Offers numerical and simulation results in each chapter in order to reflect engineering practice and demonstrate the main focus of developed analysis and synthesis approaches
Download or read book Distributed Optimization in Networked Systems written by Qingguo Lü and published by Springer Nature. This book was released on 2023-02-08 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on improving the performance (convergence rate, communication efficiency, computational efficiency, etc.) of algorithms in the context of distributed optimization in networked systems and their successful application to real-world applications (smart grids and online learning). Readers may be particularly interested in the sections on consensus protocols, optimization skills, accelerated mechanisms, event-triggered strategies, variance-reduction communication techniques, etc., in connection with distributed optimization in various networked systems. This book offers a valuable reference guide for researchers in distributed optimization and for senior undergraduate and graduate students alike.
Download or read book Game Theory for Control of Optical Networks written by Lacra Pavel and published by Birkhäuser. This book was released on 2012-04-28 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optical networks epitomize complex communication systems, and they comprise the Internet’s infrastructural backbone. The first of its kind, this book develops the mathematical framework needed from a control perspective to tackle various game-theoretical problems in optical networks. In doing so, it aims to help design control algorithms that optimally allocate the resources of these networks. With its fresh problem-solving approach, Game Theory in Optical Networks is a unique resource for researchers, practitioners, and graduate students in applied mathematics and systems/control engineering, as well as those in electrical and computer engineering.
Download or read book Splitting Algorithms Modern Operator Theory and Applications written by Heinz H. Bauschke and published by Springer Nature. This book was released on 2019-11-06 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together research articles and state-of-the-art surveys in broad areas of optimization and numerical analysis with particular emphasis on algorithms. The discussion also focuses on advances in monotone operator theory and other topics from variational analysis and nonsmooth optimization, especially as they pertain to algorithms and concrete, implementable methods. The theory of monotone operators is a central framework for understanding and analyzing splitting algorithms. Topics discussed in the volume were presented at the interdisciplinary workshop titled Splitting Algorithms, Modern Operator Theory, and Applications held in Oaxaca, Mexico in September, 2017. Dedicated to Jonathan M. Borwein, one of the most versatile mathematicians in contemporary history, this compilation brings theory together with applications in novel and insightful ways.
Download or read book Proximal Algorithms written by Neal Parikh and published by Now Pub. This book was released on 2013-11 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proximal Algorithms discusses proximal operators and proximal algorithms, and illustrates their applicability to standard and distributed convex optimization in general and many applications of recent interest in particular. Much like Newton's method is a standard tool for solving unconstrained smooth optimization problems of modest size, proximal algorithms can be viewed as an analogous tool for nonsmooth, constrained, large-scale, or distributed versions of these problems. They are very generally applicable, but are especially well-suited to problems of substantial recent interest involving large or high-dimensional datasets. Proximal methods sit at a higher level of abstraction than classical algorithms like Newton's method: the base operation is evaluating the proximal operator of a function, which itself involves solving a small convex optimization problem. These subproblems, which generalize the problem of projecting a point onto a convex set, often admit closed-form solutions or can be solved very quickly with standard or simple specialized methods. Proximal Algorithms discusses different interpretations of proximal operators and algorithms, looks at their connections to many other topics in optimization and applied mathematics, surveys some popular algorithms, and provides a large number of examples of proximal operators that commonly arise in practice.
Download or read book Large Scale Convex Optimization written by Ernest K. Ryu and published by Cambridge University Press. This book was released on 2022-12-01 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Starting from where a first course in convex optimization leaves off, this text presents a unified analysis of first-order optimization methods – including parallel-distributed algorithms – through the abstraction of monotone operators. With the increased computational power and availability of big data over the past decade, applied disciplines have demanded that larger and larger optimization problems be solved. This text covers the first-order convex optimization methods that are uniquely effective at solving these large-scale optimization problems. Readers will have the opportunity to construct and analyze many well-known classical and modern algorithms using monotone operators, and walk away with a solid understanding of the diverse optimization algorithms. Graduate students and researchers in mathematical optimization, operations research, electrical engineering, statistics, and computer science will appreciate this concise introduction to the theory of convex optimization algorithms.
Download or read book Splitting Methods in Communication Imaging Science and Engineering written by Roland Glowinski and published by Springer. This book was released on 2017-01-05 with total page 822 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about computational methods based on operator splitting. It consists of twenty-three chapters written by recognized splitting method contributors and practitioners, and covers a vast spectrum of topics and application areas, including computational mechanics, computational physics, image processing, wireless communication, nonlinear optics, and finance. Therefore, the book presents very versatile aspects of splitting methods and their applications, motivating the cross-fertilization of ideas.
Download or read book Proceedings of 2021 5th Chinese Conference on Swarm Intelligence and Cooperative Control written by Zhang Ren and published by Springer Nature. This book was released on 2022-07-29 with total page 1902 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes original, peer-reviewed research papers from the 2021 5th Chinese Conference on Swarm Intelligence and Cooperative Control (CCSICC2021), held in Shenzhen, China on January 19-22, 2022. The topics covered include but are not limited to: reviews and discussions of swarm intelligence, basic theories on swarm intelligence, swarm communication and networking, swarm perception, awareness and location, swarm decision and planning, cooperative control, cooperative guidance, swarm simulation and assessment. The papers showcased here share the latest findings on theories, algorithms and applications in swarm intelligence and cooperative control, making the book a valuable asset for researchers, engineers, and university students alike.
Download or read book The Linear Complementarity Problem written by Richard W. Cottle and published by SIAM. This book was released on 2009-08-27 with total page 781 pages. Available in PDF, EPUB and Kindle. Book excerpt: A revised edition of the standard reference on the linear complementarity problem.
Download or read book Encyclopedia of Optimization written by Christodoulos A. Floudas and published by Springer Science & Business Media. This book was released on 2008-09-04 with total page 4646 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of the Encyclopedia of Optimization is to introduce the reader to a complete set of topics that show the spectrum of research, the richness of ideas, and the breadth of applications that has come from this field. The second edition builds on the success of the former edition with more than 150 completely new entries, designed to ensure that the reference addresses recent areas where optimization theories and techniques have advanced. Particularly heavy attention resulted in health science and transportation, with entries such as "Algorithms for Genomics", "Optimization and Radiotherapy Treatment Design", and "Crew Scheduling".
Download or read book Non centralized Optimization Based Control Schemes for Large Scale Energy Systems written by W. Wicak Ananduta and published by Springer Nature. This book was released on 2021-12-11 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the development of innovative non-centralized optimization-based control schemes to solve economic dispatch problems of large-scale energy systems. Particularly, it focuses on communication and cooperation processes of local controllers, which are integral parts of such schemes. The economic dispatch problem, which is formulated as a convex optimization problem with edge‐based coupling constraints, is solved by using methodologies in distributed optimization over time-varying networks, together with distributed model predictive control, and system partitioning techniques. At first, the book describes two distributed optimization methods, which are iterative and require the local controllers to exchange information with each other at each iteration. In turn, it shows that the sequence produced by these methods converges to an optimal solution when some conditions, which include how the controllers must communicate and cooperate, are satisfied. Further, it proposes an information exchange protocol to cope with possible communication link failures. Finally, the proposed distributed optimization methods are extended to the cases with random communication networks and asynchronous updates. Overall, this book presents a set of improved predictive control and distributed optimization methods, together with a rigorous mathematical analysis of each proposed algorithms. It describes a comprehensive approach to cope with communication and cooperation issues of non-centralized control schemes and show how the improved schemes can be successfully applied to solve the economic dispatch problems of large-scale energy systems.
Download or read book Bio Inspired Computing Theories and Applications written by Linqiang Pan and published by Springer Nature. This book was released on 2022-03-23 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set (CCIS 1565 and CCIS 1566) constitutes selected and revised papers from the 16th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2021, held in Taiyuan, China, in December 2021. The 67 papers presented were thoroughly reviewed and selected from 211 submissions. The papers are organized in the following topical sections: evolutionary computation and swarm intelligence; DNA and molecular computing; machine learning and computer vision.
