Optimization algorithms
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A comprehensive introduction into optimization with an emphasis on practical algorithms for designing engineering systems
This book offers a comprehensive introduction to optimization with an emphasis on practical algorithms. The book is suitable for optimization from an engineering point of view, for which the goal is to develop a system that optimizes the set of parameters, taking into account restrictions. Readers will learn about computing approaches to solving a number of problems, including a search in multidimensional spaces, solving problems associated with many competing goals, and taking into account uncertainty in parameters. Drawings, examples and exercises reflect intuitive representations underlying mathematical approaches. The book contains specific implementations of algorithms in the Julia programming language.
The book discusses the derivatives and their generalization for multidimensional spaces, local descent methods and methods of the first and second order, which are used in combination with local descent methods, stochastic methods that bring an accident into the optimization process, linear optimization With restrictions in which both target function and restrictions are linear, surrogate models, probabilistic surrogate models and the use of probabilistic surrogate models to control optimization, optimization in conditions of uncertainty, distribution of uncertainty, optimization of expressions, interdisciplinary optimization of projects.
In the applications, the introduction of Julia programming, test functions for assessing the performance of algorithms and mathematical concepts used in the output and analysis of the discussed optimization methods are proposed. The book can be useful to students and graduate students studying mathematics, statistics, computer science and any field of technology, as well as professionals as a reference book.
About the authors
Michael Cochenderfer - Associate Professor of the Department of Aeronautics and Cosmonautics of Stanford University and the author of the book Decision Making Under Uncertain: Theory and Application.
Tim Wheeler defended his thesis at Stanford University for Safety Safety systems of unmanned vehicles and is currently developing software for the aerospace industry
This book offers a comprehensive introduction to optimization with an emphasis on practical algorithms. The book is suitable for optimization from an engineering point of view, for which the goal is to develop a system that optimizes the set of parameters, taking into account restrictions. Readers will learn about computing approaches to solving a number of problems, including a search in multidimensional spaces, solving problems associated with many competing goals, and taking into account uncertainty in parameters. Drawings, examples and exercises reflect intuitive representations underlying mathematical approaches. The book contains specific implementations of algorithms in the Julia programming language.
The book discusses the derivatives and their generalization for multidimensional spaces, local descent methods and methods of the first and second order, which are used in combination with local descent methods, stochastic methods that bring an accident into the optimization process, linear optimization With restrictions in which both target function and restrictions are linear, surrogate models, probabilistic surrogate models and the use of probabilistic surrogate models to control optimization, optimization in conditions of uncertainty, distribution of uncertainty, optimization of expressions, interdisciplinary optimization of projects.
In the applications, the introduction of Julia programming, test functions for assessing the performance of algorithms and mathematical concepts used in the output and analysis of the discussed optimization methods are proposed. The book can be useful to students and graduate students studying mathematics, statistics, computer science and any field of technology, as well as professionals as a reference book.
About the authors
Michael Cochenderfer - Associate Professor of the Department of Aeronautics and Cosmonautics of Stanford University and the author of the book Decision Making Under Uncertain: Theory and Application.
Tim Wheeler defended his thesis at Stanford University for Safety Safety systems of unmanned vehicles and is currently developing software for the aerospace industry
Author:
Author:Kochenderfer Michael
Cover:
Cover:Soft
Category:
- Category:Computer & Technology
ISBN:
ISBN:978-5-907144-76-7
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