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Название: Computational Optimization: Success in Practice
Автор: Vladislav Bukshtynov
Издательство: CRC Press
Год: 2023
Страниц: 415
Язык: английский
Формат: pdf (true)
Размер: 18.9 MB
This textbook offers a guided tutorial that reviews the theoretical fundamentals while going through the practical examples used for constructing the computational frame, applied to various real-life models. Computational Optimization: Success in Practice will lead the readers through the entire process. They will start with the simple calculus examples of fitting data and basics of optimal control methods and end up constructing a multi-component framework for running PDE-constrained optimization. This framework will be assembled piece by piece; the readers may apply this process at the levels of complexity matching their current projects or research needs. The main optimization framework builds through the course exercises and centers on MATLAB. This book will prove valuable to graduate students of math, Computer Science, engineering, and all who explore optimization techniques at different levels for educational or research purposes. It will benefit many professionals in academic and industry-related research: professors, researchers, postdoctoral fellows, and the personnel of R&D departments.
Автор: Vladislav Bukshtynov
Издательство: CRC Press
Год: 2023
Страниц: 415
Язык: английский
Формат: pdf (true)
Размер: 18.9 MB
This textbook offers a guided tutorial that reviews the theoretical fundamentals while going through the practical examples used for constructing the computational frame, applied to various real-life models. Computational Optimization: Success in Practice will lead the readers through the entire process. They will start with the simple calculus examples of fitting data and basics of optimal control methods and end up constructing a multi-component framework for running PDE-constrained optimization. This framework will be assembled piece by piece; the readers may apply this process at the levels of complexity matching their current projects or research needs. The main optimization framework builds through the course exercises and centers on MATLAB. This book will prove valuable to graduate students of math, Computer Science, engineering, and all who explore optimization techniques at different levels for educational or research purposes. It will benefit many professionals in academic and industry-related research: professors, researchers, postdoctoral fellows, and the personnel of R&D departments.