Jan snyman (31 resultados)

Softcover/Paperback. Condición: Sehr gut. 280 p. Very good. Shrink wrapped. / Sehr guter Zustand. In Folie verschweißt. Sprache: Englisch Gewicht in Gramm: 604.

Soft cover. Condición: New. 1st Edition. 257 pages. new.

15 x 23 cm. 278 pages. Paperback. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch.

Softcover. Condición: Good. No Jacket. Reprint. Afrikaans text. The wraps are shelf rubbed with marks and light creasing. The binding is secure. The pages are browned. Tippex inscription on the front end page. No other ink inscriptions or annotations. JHK. Our orders are shipped using tracked courier delivery services.…

Condición: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Condición: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Condición: New.

Condición: New.

Condición: New.

Blanda. Condición: New. Estado de la sobrecubierta: Nuevo. 0. This book presents basic optimization principles and gradient-based algorithms to a general audience, in a brief and easy-to-read form without neglecting rigour. The work should enable the professional to apply optimization theory and algorithms to his own particular practical field of interest, be it engineering, physics, chemistry, or business economics. Most importantly, for the first time in a relatively brief and introductory work, due attention is paid to the difficulties?such as noise, discontinuities, expense of function evaluations, and the existence of multiple minima?that often unnecessarily inhibit the use of gradient-based methods. In a separate chapter on new gradient-based methods developed by the author and his coworkers, it is shown how these difficulties may be overcome without losing the desirable features of classical gradient-based methods. Audience. It is intended that this book be used in senior- to graduate-level semester courses in optimization, as offered in mathematics, engineering, computer science, and operations research departments, and also to be useful to practising professionals in the workplace. 480 gr. No Aplica (ilustrador). Libro.…

Original-Pappband. Condición: Sehr gut. gr8 Original-Pappband 2nd Ed. en (Springer Optimization and Its Applications, Vol. 133) XXVI, 372 pp.

Condición: New. pp. 400.

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.…

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. …

Paperback. Condición: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Softcover. Condición: gut. 2018. Practical Mathematical Optimization. Basic Optimization Theory an Gradient-Based Algorithms In deutscher Sprache. pages.

Hardcover. Condición: Near Fine. 1st Edition. Landscape 220 x 290mm. Glazed boards clean but with sl. bump to bottom outer corner. 89pp. illus. No prev ownership marks or o/w. Price label to back. Scarce title.

Condición: new. Questo è un articolo print on demand.

Condición: new. Questo è un articolo print on demand.

PF. Condición: New. This item is printed on demand. Brand new book, sourced directly from publisher. Dispatch time is 6-7 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

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.…

Buch. 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. 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. …

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. 278 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.

Buch. Condición: Neu. nach der Bestellung gedruckt 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.…

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.…

Buch. 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.…