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Titlebook: Optimization and Optimal Control; Theory and Applicati Altannar Chinchuluun,Panos M. Pardalos,Ider Tseve Book 2010 Springer Science+Busine

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發(fā)表于 2025-3-21 19:11:37 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Optimization and Optimal Control
副標(biāo)題Theory and Applicati
編輯 Altannar Chinchuluun,Panos M. Pardalos,Ider Tseve
視頻videohttp://file.papertrans.cn/704/703227/703227.mp4
概述Collection of selected contributions giving a state-of-the-art account of recent developments in the field.Covers a broad range of topics in optimization and optimal control, including unique applicat
叢書(shū)名稱Springer Optimization and Its Applications
圖書(shū)封面Titlebook: Optimization and Optimal Control; Theory and Applicati  Altannar Chinchuluun,Panos M. Pardalos,Ider Tseve Book 2010 Springer Science+Busine
描述.During the last four decades there has been a remarkable development in optimization and optimal control. Due to its wide variety of applications, many scientists and researchers have paid attention to fields of optimization and optimal control. A huge number of new theoretical, algorithmic, and computational results have been observed in the last few years. This book gives the latest advances, and?due to the rapid development of these fields, there are no other recent publications on the same topics...Key features:..Provides a collection of selected contributions giving a state-of-the-art account of recent developments in the field..Covers a broad range of topics in optimization and optimal control, including unique applications..Includes chapters written by experts in their respective disciplines..Appeals to a broad audience of?researchers, practitioners, and advanced graduate students in applied mathematics and engineering.
出版日期Book 2010
關(guān)鍵詞Maxima; algorithms; calculus; control; evolution; evolutionary algorithm; global optimization; learning; mat
版次1
doihttps://doi.org/10.1007/978-0-387-89496-6
isbn_softcover978-1-4614-2624-0
isbn_ebook978-0-387-89496-6Series ISSN 1931-6828 Series E-ISSN 1931-6836
issn_series 1931-6828
copyrightSpringer Science+Business Media, LLC 2010
The information of publication is updating

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Analysis of Differential Inclusions: Feedback Control Method,method of feedback control. They adaptively take into account inaccurate measurements of phase trajectories and are regularized in the following sense: the more precise is incoming information, the better is the algorithm’s output.
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,A Game Theoretic Algorithm to Solve Riccati and Hamilton—Jacobi—Bellman—Isaacs (HJBI) Equations in .. Riccati equations or Hamilton—Jacobi—Bellman (HJB) equations. The algorithms have some advantages such as a simple initialization, local quadratic rate of convergence, and a natural game theoretic interpretation. Some numerical examples are given to demonstrate advantages of our algorithm.
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Book 2010ny scientists and researchers have paid attention to fields of optimization and optimal control. A huge number of new theoretical, algorithmic, and computational results have been observed in the last few years. This book gives the latest advances, and?due to the rapid development of these fields, t
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1931-6828 optimization and optimal control, including unique applicat.During the last four decades there has been a remarkable development in optimization and optimal control. Due to its wide variety of applications, many scientists and researchers have paid attention to fields of optimization and optimal co
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On Equilibrium Problems,, and variational inequalities. Then, some classical and new results together with their proofs concerning existence of solutions of equilibrium problems are exposed. The existence of approximate solutions via Ekeland’s variational principle – extended to equilibrium problems – is treated within the last part of the chapter.
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General Quadratic Programming and Its Applications in Response Surface Analysis,propose finite algorithms for solving those problems. As application, some real practical problems arising in the response surface, one of the main part of design of experiment, have been solved numerically by the algorithms.
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Online Adaptive Optimal Control Based on Reinforcement Learning,thm is derived in a continuous-time framework. The algorithm is an online approach to policy iterations based on an adaptive critic structure to find an approximate solution to the state feedback, infinite-horizon, optimal control problem.
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