Practical Mathematical Optimization: An Introduction to Basic Optimization Theory and Classical and New Gradient-Based Algorithms: Applied Optimization, cartea 97
Autor Jan Snymanen Limba Engleză Paperback – 29 noi 2005
Din seria Applied Optimization
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Specificații
ISBN-13: 9780387298245
ISBN-10: 038729824X
Pagini: 258
Ilustrații: XX, 258 p.
Dimensiuni: 155 x 235 x 16 mm
Greutate: 0.48 kg
Ediția:1st ed. 2005. Corr. 2nd printing 2005
Editura: Springer Us
Colecția Springer
Seria Applied Optimization
Locul publicării:New York, NY, United States
ISBN-10: 038729824X
Pagini: 258
Ilustrații: XX, 258 p.
Dimensiuni: 155 x 235 x 16 mm
Greutate: 0.48 kg
Ediția:1st ed. 2005. Corr. 2nd printing 2005
Editura: Springer Us
Colecția Springer
Seria Applied Optimization
Locul publicării:New York, NY, United States
Public țintă
ResearchCuprins
Line Search Descent Methods for Unconstrained Minimization.- Standard Methods for Constrained Optimization.- New Gradient-Based Trajectory and Approximation Methods.- Example Problems.- Some Theorems.
Textul de pe ultima copertă
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.
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.
Caracteristici
Presents the theory in a straightforward readable manner This is the first compact reference to address difficulties that inhibit broad use of gradient-based methods Shows how to apply optimization theory and algorithms in such fields as engineering, physics, chemistry, or business economics Includes theorems of particular interest and many worked-out example problems Includes supplementary material: sn.pub/extras