The Mathematics of Nonlinear Programming (Undergraduate Texts in Mathematics). Este artículo no está disponible.
Peressini, Anthony L.; Sullivan, Francis E.; Uhl, J.J. Jr.
11 valoraciones de Goodreads
Idioma: inglés
Editorial: Springer, 1988
- Tapa dura
- Usado

Librería: Dream Books Co., Denver, CO, Estados Unidos de AmericaDream Books Co.
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Descripción del artículo del vendedor
Gently used with minimal wear on the corners and cover. A few pages may contain light highlighting or writing, but the text remains fully legible. Dust jacket may be missing, and supplemental materials like CDs or codes may not be included. May be ex-library with library markings. Ships promptly.
N° de ref. del artículo DBV.0387966145.G
- Título
- The Mathematics of Nonlinear Programming (Undergraduate Texts in Mathematics)
- Autor
- Peressini, Anthony L.; Sullivan, Francis E.; Uhl, J.J. Jr.
- Editorial
- Springer
- Año de publicación
- 1988
- Estado
- good
- Encuadernación
- Encuadernación de tapa dura
- Idioma
- inglés
- ISBN 10
- 0387966145
- ISBN 13
- 9780387966144
- Edición
- 2ª Edición
Nonlinear programming provides an excellent opportunity to explore an interesting variety of pure and solidly applicable mathematics, numerical analysis, and computing. This text develops some of the ideas and techniques involved in the optimization methods using calculus, leading to the study of convexity. This is followed by material on basic numerical methods, least squares, the Karush-Kuhn-Tucker theorem, penalty functions, and Lagrange multipliers. The authors have aimed their presentation at the student who has a working knowledge of matrix algebra and advanced calculus, but has had no previous exposure to optimization.
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Reseña del editor
Nonlinear programming provides an excellent opportunity to explore an interesting variety of pure and solidly applicable mathematics, numerical analysis, and computing. This text develops some of the ideas and techniques involved in the optimization methods using calculus, leading to the study of convexity. This is followed by material on basic numerical methods, least squares, the Karush-Kuhn-Tucker theorem, penalty functions, and Lagrange multipliers. The authors have aimed their presentation at the student who has a working knowledge of matrix algebra and advanced calculus, but has had no previous exposure to optimization.
“Acerca de” puede pertenecer a otra edición de este título.
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