9783030084868 - Practical Mathematical Optimization: Basic Optimization Theory and Gradient-Based Algorithms: 133 (Springer Optimization and Its Applications) de Snyman, Jan A; Wil... (12 resultados)

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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, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

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 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.

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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 principles 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.

Condición: New. Print on Demand pp. 400.

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&nbspmaterial on gradient-based methods,&nbspalgorithm implementation via Python, and&nbspbasic optimization principlesCovers fu.

Condición: New. PRINT ON DEMAND pp. 400.

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 principles 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.