Optimization And Its Applications In Control And Data Sciences
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Optimization And Its Applications In Control And Data Sciences
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Author : Boris Goldengorin
language : en
Publisher: Springer
Release Date : 2016-09-29
Optimization And Its Applications In Control And Data Sciences written by Boris Goldengorin and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-29 with Mathematics categories.
This book focuses on recent research in modern optimization and its implications in control and data analysis. This book is a collection of papers from the conference “Optimization and Its Applications in Control and Data Science” dedicated to Professor Boris T. Polyak, which was held in Moscow, Russia on May 13-15, 2015. This book reflects developments in theory and applications rooted by Professor Polyak’s fundamental contributions to constrained and unconstrained optimization, differentiable and nonsmooth functions, control theory and approximation. Each paper focuses on techniques for solving complex optimization problems in different application areas and recent developments in optimization theory and methods. Open problems in optimization, game theory and control theory are included in this collection which will interest engineers and researchers working with efficient algorithms and software for solving optimization problems in market and data analysis. Theoreticians in operations research, applied mathematics, algorithm design, artificial intelligence, machine learning, and software engineering will find this book useful and graduate students will find the state-of-the-art research valuable.
Introduction To Applied Optimization
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Author : Urmila Diwekar
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Introduction To Applied Optimization written by Urmila Diwekar and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Mathematics categories.
Provides well-written self-contained chapters, including problem sets and exercises, making it ideal for the classroom setting; Introduces applied optimization to the hazardous waste blending problem; Explores linear programming, nonlinear programming, discrete optimization, global optimization, optimization under uncertainty, multi-objective optimization, optimal control and stochastic optimal control; Includes an extensive bibliography at the end of each chapter and an index; GAMS files of case studies for Chapters 2, 3, 4, 5, and 7 are linked to http://www.springer.com/math/book/978-0-387-76634-8; Solutions manual available upon adoptions. Introduction to Applied Optimization is intended for advanced undergraduate and graduate students and will benefit scientists from diverse areas, including engineers.
Approximation And Optimization
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Author : Ioannis C. Demetriou
language : en
Publisher: Springer
Release Date : 2020-08-14
Approximation And Optimization written by Ioannis C. Demetriou and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-14 with Mathematics categories.
This book focuses on the development of approximation-related algorithms and their relevant applications. Individual contributions are written by leading experts and reflect emerging directions and connections in data approximation and optimization. Chapters discuss state of the art topics with highly relevant applications throughout science, engineering, technology and social sciences. Academics, researchers, data science practitioners, business analysts, social sciences investigators and graduate students will find the number of illustrations, applications, and examples provided useful. This volume is based on the conference Approximation and Optimization: Algorithms, Complexity, and Applications, which was held in the National and Kapodistrian University of Athens, Greece, June 29–30, 2017. The mix of survey and research content includes topics in approximations to discrete noisy data; binary sequences; design of networks and energy systems; fuzzy control; large scale optimization; noisy data; data-dependent approximation; networked control systems; machine learning ; optimal design; no free lunch theorem; non-linearly constrained optimization; spectroscopy.
Global Optimization In Action
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Author : János D. Pintér
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-14
Global Optimization In Action written by János D. Pintér and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-14 with Mathematics categories.
In science, engineering and economics, decision problems are frequently modelled by optimizing the value of a (primary) objective function under stated feasibility constraints. In many cases of practical relevance, the optimization problem structure does not warrant the global optimality of local solutions; hence, it is natural to search for the globally best solution(s). Global Optimization in Action provides a comprehensive discussion of adaptive partition strategies to solve global optimization problems under very general structural requirements. A unified approach to numerous known algorithms makes possible straightforward generalizations and extensions, leading to efficient computer-based implementations. A considerable part of the book is devoted to applications, including some generic problems from numerical analysis, and several case studies in environmental systems analysis and management. The book is essentially self-contained and is based on theauthor's research, in cooperation (on applications) with a number of colleagues. Audience: Professors, students, researchers and other professionals in the fields of operations research, management science, industrial and applied mathematics, computer science, engineering, economics and the environmental sciences.
Convex Optimization
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Author : Stephen P. Boyd
language : en
Publisher: Cambridge University Press
Release Date : 2004-03-08
Convex Optimization written by Stephen P. Boyd and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-03-08 with Business & Economics categories.
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.
Data Driven Science And Engineering
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Author : Steven L. Brunton
language : en
Publisher: Cambridge University Press
Release Date : 2022-05-05
Data Driven Science And Engineering written by Steven L. Brunton and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-05 with Computers categories.
A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
Robust Discrete Optimization And Its Applications
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Author : Panos Kouvelis
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Robust Discrete Optimization And Its Applications written by Panos Kouvelis and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Mathematics categories.
This book deals with decision making in environments of significant data un certainty, with particular emphasis on operations and production management applications. For such environments, we suggest the use of the robustness ap proach to decision making, which assumes inadequate knowledge of the decision maker about the random state of nature and develops a decision that hedges against the worst contingency that may arise. The main motivating factors for a decision maker to use the robustness approach are: • It does not ignore uncertainty and takes a proactive step in response to the fact that forecasted values of uncertain parameters will not occur in most environments; • It applies to decisions of unique, non-repetitive nature, which are common in many fast and dynamically changing environments; • It accounts for the risk averse nature of decision makers; and • It recognizes that even though decision environments are fraught with data uncertainties, decisions are evaluated ex post with the realized data. For all of the above reasons, robust decisions are dear to the heart of opera tional decision makers. This book takes a giant first step in presenting decision support tools and solution methods for generating robust decisions in a variety of interesting application environments. Robust Discrete Optimization is a comprehensive mathematical programming framework for robust decision making.
Advances And Trends In Optimization With Engineering Applications
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Author : Tamas Terlaky
language : en
Publisher: SIAM
Release Date : 2017-04-26
Advances And Trends In Optimization With Engineering Applications written by Tamas Terlaky and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-26 with Mathematics categories.
Optimization is of critical importance in engineering. Engineers constantly strive for the best possible solutions, the most economical use of limited resources, and the greatest efficiency. As system complexity increases, these goals mandate the use of state-of-the-art optimization techniques. In recent years, the theory and methodology of optimization have seen revolutionary improvements. Moreover, the exponential growth in computational power, along with the availability of multicore computing with virtually unlimited memory and storage capacity, has fundamentally changed what engineers can do to optimize their designs. This is a two-way process: engineers benefit from developments in optimization methodology, and challenging new classes of optimization problems arise from novel engineering applications. Advances and Trends in Optimization with Engineering Applications reviews 10 major areas of optimization and related engineering applications, providing a broad summary of state-of-the-art optimization techniques most important to engineering practice. Each part provides a clear overview of a specific area and discusses a range of real-world problems. The book provides a solid foundation for engineers and mathematical optimizers alike who want to understand the importance of optimization methods to engineering and the capabilities of these methods.
Advanced And Optimization Based Sliding Mode Control Theory And Applications
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Author : Antonella Ferrara
language : en
Publisher: SIAM
Release Date : 2019-07-01
Advanced And Optimization Based Sliding Mode Control Theory And Applications written by Antonella Ferrara and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-01 with Mathematics categories.
A compendium of the authors recently published results, this book discusses sliding mode control of uncertain nonlinear systems, with a particular emphasis on advanced and optimization based algorithms. The authors survey classical sliding mode control theory and introduce four new methods of advanced sliding mode control. They analyze classical theory and advanced algorithms, with numerical results complementing the theoretical treatment. Case studies examine applications of the algorithms to complex robotics and power grid problems. Advanced and Optimization Based Sliding Mode Control: Theory and Applications is the first book to systematize the theory of optimization based higher order sliding mode control and illustrate advanced algorithms and their applications to real problems. It presents systematic treatment of event-triggered and model based event-triggered sliding mode control schemes, including schemes in combination with model predictive control, and presents adaptive algorithms as well as algorithms capable of dealing with state and input constraints. Additionally, the book includes simulations and experimental results obtained by applying the presented control strategies to real complex systems. This book is suitable for students and researchers interested in control theory. It will also be attractive to practitioners interested in implementing the illustrated strategies. It is accessible to anyone with a basic knowledge of control engineering, process physics, and applied mathematics.
Machine Learning Optimization And Data Science
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Author : Giuseppe Nicosia
language : en
Publisher: Springer Nature
Release Date : 2025-03-03
Machine Learning Optimization And Data Science written by Giuseppe Nicosia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-03 with Computers categories.
The three-volume set LNAI 15508-15510 constitutes the refereed proceedings of the 10th International Conference on Machine Learning, Optimization, and Data Science, LOD 2024, held in Castiglione della Pescaia, Italy, during September 22–25, 2024. This year, in the LOD Proceedings decided to also include the papers of the fourth edition of the Symposium on Artificial Intelligence and Neuroscience (ACAIN 2024). The 79 full papers included in this book were carefully reviewed and selected from 127 submissions. The LOD 2024 proceedings focus on machine learning, deep learning, AI, computational optimization, neuroscience and big data that includes invited talks, tutorial talks, special sessions, industrial tracks, demonstrations and oral and poster presentations of refereed papers.