by A. Ben-Tal, L. El Ghaoui, A. Nemirovski
Publisher: Princeton University Press 2009
Number of pages: 564
Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology. 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 the subject.
Home page url
Download or read it online for free here:
by Guido Schaefer - Utrecht University
From the table of contents: Preliminaries (Optimization Problems); Minimum Spanning Trees; Matroids; Shortest Paths; Maximum Flows; Minimum Cost Flows; Matchings; Integrality of Polyhedra; Complexity Theory; Approximation Algorithms.
by Dariush Khezrimotlagh - arXiv
I wrote this book as a self-teaching tool to assist every teacher, student, mathematician or non-mathematician, and to support their understanding of the elementary concepts on assessing the performance of a set of homogenous firms ...
by U. Helmke, J. B. Moore - Springer
Aimed at mathematics and engineering graduate students and researchers in the areas of optimization, dynamical systems, control systems, signal processing, and linear algebra. The problems solved are those of linear algebra and linear systems theory.
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.