A numerical comparison of some modified controlled random search algorithms

In this paper we propose a new version of the Controlled Random Search (CRS) algorithm of Price. The new algorithm has been tested on thirteen global optimization test problems. Numerical experiments indicate that the resulting algorithm performs considerably better than the earlier versions of the CRS algorithms. The algorithm, therefore, could offer a reasonable alternative to many currently available stochastic algorithms, especially for problems requiring 'direct search' type methods. Also a classification of the CRS algorithms is made based on 'global technique' - 'local technique' and the relative performance of classes is numerically explored.