9783030084868 - practical mathematical optimization: basic optimization theory and gradient-based algorithms: 133 (springer optimization and its applications) de snyman, jan a; wilke, daniel n (11 resultados)
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Editorial: Springer, 2019
Serie: Springer Optimization and Its Applications, Libro 123 de 176. Libro 123 de 176 - Springer Optimization and Its Applications
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Taschenbuch. Condición: Neu. Practical Mathematical Optimization | Basic Optimization Theory and Gradient-Based Algorithms | Jan A Snyman (u. a.) | Taschenbuch | Springer Optimization and Its Applications | xxvi | Englisch | 2019 | Springer | EAN 9783030084868 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergarten…str. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Idioma: Inglés
Editorial: Springer, Springer, 2019
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This textbook presents a wide range of tools for a course in mathematical optimization for upper undergraduate and graduate students in mathematics, engineering, computer science, and other applied sciences. Basic optimization principles are presen…ted with emphasis on gradient-based numerical optimization strategies and algorithms for solving both smooth and noisy discontinuous optimization problems. Attention is also paid to the difficulties of expense of function evaluations and the existence of multiple minima that often unnecessarily inhibit the use of gradient-based methods. This second edition addresses further advancements ofgradient-only optimization strategies to handlediscontinuities in objective functions. New chapters discuss the construction of surrogate models as well as new gradient-only solution strategies andnumerical optimizationusing Python. A special Python module is electronically available (via springerlink) that makes the new algorithms featured in the text easily accessible and directly applicable. Numerical examples and exercises are included to encourage senior- to graduate-level students to plan, execute, and reflect on numerical investigations. By gaining a deep understanding of the conceptual material presented, students, scientists, and engineers will be able to develop systematic and scientific numerical investigative skills.
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Editorial: Springer, 2019
Serie: Springer Optimization and Its Applications, Libro 123 de 176. Libro 123 de 176 - Springer Optimization and Its Applications
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Editorial: Springer, Springer Jan 2019, 2019
Serie: Springer Optimization and Its Applications, Libro 123 de 176. Libro 123 de 176 - Springer Optimization and Its Applications
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This textbook presents a wide range of tools for a course in mathematical optimization for upper undergraduate and graduate students in mathematics, engineering, computer science, and other applied sciences. Basic optimization princ…iples are presented with emphasis on gradient-based numerical optimization strategies and algorithms for solving both smooth and noisy discontinuous optimization problems. Attention is also paid to the difficulties of expense of function evaluations and the existence of multiple minima that often unnecessarily inhibit the use of gradient-based methods. This second edition addresses further advancements ofgradient-only optimization strategies to handlediscontinuities in objective functions. New chapters discuss the construction of surrogate models as well as new gradient-only solution strategies andnumerical optimizationusing Python. A special Python module is electronically available (via springerlink) that makes the new algorithms featured in the text easily accessible and directly applicable. Numerical examples and exercises are included to encourage senior- to graduate-level students to plan, execute, and reflect on numerical investigations. By gaining a deep understanding of the conceptual material presented, students, scientists, and engineers will be able to develop systematic and scientific numerical investigative skills. 400 pp. Englisch.
Idioma: Inglés
Editorial: Springer, 2019
Serie: Springer Optimization and Its Applications, Libro 123 de 176. Libro 123 de 176 - Springer Optimization and Its Applications
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Condición: New. Print on Demand pp. 400.
Idioma: Inglés
Editorial: Springer International Publishing, 2019
Serie: Springer Optimization and Its Applications, Libro 123 de 176. Libro 123 de 176 - Springer Optimization and Its Applications
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Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Guides readers to understand processes and strategies in real world optimization problemsContains new material on gradient-based methods, algorithm implementation via Python, and b…asic optimization principlesCovers fu.
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Editorial: Springer, 2019
Serie: Springer Optimization and Its Applications, Libro 123 de 176. Libro 123 de 176 - Springer Optimization and Its Applications
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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Condición: New. PRINT ON DEMAND pp. 400.
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Editorial: Springer, Springer Jan 2019, 2019
Serie: Springer Optimization and Its Applications, Libro 123 de 176. Libro 123 de 176 - Springer Optimization and Its Applications
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This textbook presents a wide range of tools for a course in mathematical optimization for upper undergraduate and graduate students in mathematics, engineering, computer science, and other applied sciences. Basic optimization principle…s are presented with emphasis on gradient-based numerical optimization strategies and algorithms for solving both smooth and noisy discontinuous optimization problems. Attention is also paid to the difficulties of expense of function evaluations and the existence of multiple minima that often unnecessarily inhibit the use of gradient-based methods. This second edition addresses further advancements of gradient-only optimization strategies to handle discontinuities in objective functions. New chapters discuss the construction of surrogate models as well as new gradient-only solution strategies and numerical optimization using Python. A special Python module is electronically available (via springerlink) that makes the new algorithms featured in the text easily accessible and directly applicable. Numerical examples and exercises are included to encourage senior- to graduate-level students to plan, execute, and reflect on numerical investigations. By gaining a deep understanding of the conceptual material presented, students, scientists, and engineers will be able to develop systematic and scientific numerical investigative skills.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 400 pp. Englisch.
