Computer and Information Science » Numerical Analysis and Scientific Computing

Stochastic Optimization - Seeing the Optimal for the Uncertain

Edited by Ioannis Dritsas, ISBN 978-953-307-829-8, 488 pages, Publisher: InTech, Chapters published February 28, 2011 under CC BY-NC-SA 3.0 license
DOI: 10.5772/623

Stochastic Optimization Algorithms have become essential tools in solving a wide range of difficult and critical optimization problems. Such methods are able to find the optimum solution of a problem with uncertain elements or to algorithmically incorporate uncertainty to solve a deterministic problem. They even succeed in “fighting uncertainty with uncertainty”. This book discusses theoretical aspects of many such algorithms and covers their application in various scientific fields.