Computational Issues in High Performance Software for Nonlinear Optimization

Computational Issues in High Performance Software for Nonlinear Optimization
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Murli A., Torardo G.

A special issue of , v.7, no.1 (1997), containing papers from a June 1995 conference held in Capri, Italy. Papers overview recent developments related to software for nonlinear optimization, reflecting different perspectives on well-established algorithms for nonlinear problems, fast algorithms for large-scale optimization problems, direct methods for solution of sparse linear algebra problems, and LCP solvers.

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Real-Time Optimization by Extremum-Seeking Control

Real-Time Optimization by Extremum-Seeking Control
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Ariyur K.B., Kristic M.

An up-close look at the theory behind and application of extremum seeking Originally developed as a method of adaptive control for hard-to-model systems, extremum seeking solves some of the same problems as today's neural network techniques, but in a more rigorous and practical way. Following the resurgence in popularity of extremum-seeking control in aerospace and automotive engineering, Real-Time Optimization by Extremum-Seeking Control presents the theoretical foundations and selected applications of this method of real-time optimization. Written by authorities in the field and pioneers in adaptive nonlinear control systems, this book presents both significant theoretic value and important practical potential. Filled with in-depth insight and expert advice, Real-Time Optimization by Extremum-Seeking Control:

* Develops optimization theory from the points of dynamic feedback and adaptation
* Builds a solid bridge between the classical optimization theory and modern feedback and adaptation techniques
* Provides a collection of useful tools for problems in this complex area
* Presents numerous applications of this powerful methodology
* Demonstrates the immense potential of this methodology for future theory development and applications Real-Time Optimization by Extremum-Seeking Control is an important resource for both students and professionals in all areas of engineering-electrical, mechanical, aerospace, chemical, biomedical-and is also a valuable reference for practicing control engineers.

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Iterative Methods for Optimization

Iterative Methods for Optimization
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Kelley C. T.

This book presents a carefully selected group of methods for unconstrained and bound constrained optimization problems and analyzes them in depth both theoretically and algorithmically. It focuses on clarity in algorithmic description and analysis rather than generality, and while it provides pointers to the literature for the most general theoretical results and robust software, the author thinks it is more important that readers have a complete understanding of special cases that convey essential ideas. A companion to Kelley’s book, Iterative Methods for Linear and Nonlinear Equations (SIAM, 1995), this book contains many exercises and examples and can be used as a text, a tutorial for self-study, or a reference.

Iterative Methods for Optimization does more than cover traditional gradient-based optimization: it is the first book to treat sampling methods, including the Hooke–Jeeves, implicit filtering, MDS, and Nelder–Mead schemes in a unified way, and also the first book to make connections between sampling methods and the traditional gradient-methods. Each of the main algorithms in the text is described in pseudocode, and a collection of MATLAB codes is available. Thus, readers can experiment with the algorithms in an easy way as well as implement them in other languages.

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Linear Programming

Linear Programming
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Ourmedia

An introduction to Dantzig's simplex method of finding optimal solutions.

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Introduction to Numerical Linear Algebra and Optimisation (Cambridge Texts in Applied Mathematics)

Introduction to Numerical Linear Algebra and Optimisation (Cambridge Texts in Applied Mathematics)
by: Philippe G. Ciarlet

Details

# Paperback: 452 pages
# Publisher: Cambridge University Press (August 25, 1989)
# Language: English
# ISBN-10: 0521339847
# ISBN-13: 978-0521339841

Description

Based on courses taught to advanced undergraduate students, this book offers a broad introduction to the methods of numerical linear algebra and optimization. The prerequisites are familiarity with the basic properties of matrices, finite-dimensional vector spaces and advanced calculus, and some exposure to fundamental notions from functional analysis. The book is divided into two parts. The first part deals with numerical linear algebra (numerical analysis of matrices, direct and indirect methods for solving linear systems, calculation of eigenvalues and eigenvectors) and the second, optimizations (general algorithms, linear and nonlinear programming). Summaries of basic mathematics are provided, proof of theorems are complete yet kept as simple as possible, applications from physics and mechanics are discussed, a great many exercises are included, and there is a useful guide to further reading.

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