Iterative Methods for Optimization
by C.T. Kelley
Publisher: Society for Industrial Mathematics 1987
Number of pages: 188
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.
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by A. Ben-Tal, L. El Ghaoui, A. Nemirovski - Princeton University Press
Written by the principal developers of robust optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of this relatively new approach to optimization.
by P.-A. Absil, R. Mahony, R. Sepulchre - Princeton University Press
Many science and engineering problems can be rephrased as optimization problems on matrix search spaces endowed with a manifold structure. This book shows how to exploit the structure of such problems to develop efficient numerical algorithms.
by Ian Craw - University of Aberdeen
The book describes the simplex algorithm and shows how it can be used to solve real problems. It shows how previous results in linear algebra give a framework for understanding the simplex algorithm and describes other optimization algorithms.
by Jim Burke - University of Washington
These are notes for an introductory course in linear programming. The four basic components of the course are modeling, solution methodology, duality theory, and sensitivity analysis. We focus on the simplex algorithm due to George Dantzig.