Computational Optimization (PDF)
Success in Practice
(Sprache: Englisch)
This textbook offers a guided tutorial reviewing the theoretical fundamentals while going through the practical examples used for constructing the computational frame, applied to various real-life models.
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This textbook offers a guided tutorial reviewing the theoretical fundamentals while going through the practical examples used for constructing the computational frame, applied to various real-life models.
Autoren-Porträt von Vladislav Bukshtynov
Dr. Vladislav Bukshtynov holds a Ph.D. degree in Computational Engineering & Science from McMaster University. He is an Assistant Professor at the Dept. of Mathematical Sciences of Florida Institute of Technology. He completed a 3-year postdoctoral term at the Dept. of Energy Resources Engineering of Stanford University. He actively teaches and advises students from various fields: applied and computational math, operations research, different engineering majors. His teaching experience includes Multivariable Calculus, Honors ODE/PDE courses for undergrad students; Applied Discrete Math, Linear/Nonlinear Optimization for senior undergrads and graduates. As a researcher, Dr. Bukshtynov leads his research group with several dynamic scientific directions and ongoing collaborations for various cross-institutional and interdisciplinary projects. His current interests lie in but are not limited to the areas of applied and computational mathematics focusing on combining theoretical and numerical methods for various problems in computational/numerical optimization, control theory, and inverse problems.
Bibliographische Angaben
- Autor: Vladislav Bukshtynov
- 2023, 1. Auflage, 414 Seiten, Englisch
- Verlag: Taylor & Francis
- ISBN-10: 1000834727
- ISBN-13: 9781000834727
- Erscheinungsdatum: 17.02.2023
Abhängig von Bildschirmgrösse und eingestellter Schriftgrösse kann die Seitenzahl auf Ihrem Lesegerät variieren.
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- Dateiformat: PDF
- Grösse: 18 MB
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Sprache:
Englisch
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