Practical Mathematical Optimization

An Introduction to Basic Optimization Theory and Classical and New Gradient-Based Algorithms

Jan A. Snyman

278 pages, parution le 07/03/2006

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Résumé

This book presents basic optimization principles and gradient-based algorithms to a general audience in a brief and easy-to-read form, without neglecting rigor. The work should enable professionals to apply optimization theory and algorithms to their own particular practical fields 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.

Written for: Students taking senior- to graduate-level semester courses in optimization, as offered in mathematics, engineering, computer science, and operations research departments; practising professionals in the workplace

Sommaire

Introduction
Line Search Descent Methods for Unconstrained Minimization
Standard Methods for Constrained Optimization
New Gradient-Based Trajectory and Approximation Methods
Example Problems
Some Theorems
The Simplex Method for Linear Programming Problems

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	Jan A. Snyman
Parution	07/03/2006
Nb. de pages	278
Format	15,5 x 23,5
Couverture	Broché
Poids	475g
Intérieur	Noir et Blanc
EAN13	9780387298245
ISBN13	978-0-387-29824-5