Some variants of the controlled random search algorithm for global optimization P. Kaelo and M. M. Ali Abstract Some modiﬁcations are suggested to the controlled random search (crs) algorithm for global optimization. We introduce new trial point generation schemes in crs, in particular, point generation schemes using linear interpolation and mutation. However, central to our modiﬁcations is the probabilistic adaptation of point generation schemes within the crs algo- rithm. A numerical study is carried out using a set of 50 test problems many of which are in- spired by practical applications. Numerical experiments indicate that the resulting algorithms are considerably better than the previous versions. The new crs algorithms are also compared with the DIRECT algorithm developed by Jones et. al. [4]. The comparison shows that the crs algorithms are better than the DIRECT algorithm in high dimensional problems. Thus, they offer a reasonable alternative to many currently available stochastic algorithms, especially for problems requiring ‘direct search type’ methods. Keywords: Global optimization, direct search methods, linear interpolation, probabilistic adaptation. ————————————————– Postgraduate Student, School of Computational and Applied Mathematics, Witwatersrand University, 1 Jan Smuts Avenue, Johannesburg, South Africa. Associate Professor, School of Computational and Applied Mathematics, Witwatersrand University, 1 Jan Smuts Avenue, Johannesburg, South Africa. 1