A general-purpose global optimizer: Implimentation and applications

Abstract

This paper, written from a user stand-point, advocates the Adaptive Random Search strategy as an efficient tool for global optimization. First is presented a brief overview of the various types of methods available in the literature for global optimization, and practical advantages of the random search approach are advanced. Some modifications, which were found to improve the efficiency and versatility of the method, and a detailed description of the practical implementation of the resulting algorithm are presented. The routine is used first to treat seven test-cases from the literature for comparison purposes. Then two examples are treated related to automatic control theory. The first one is a parameter estimation problem. the second one a control problem. Finally a practical application of the method to automated registration in medical nuclear imagery is presented.