An approach to continuous optimization by the Intelligent Water Drops algorithm

In this paper, the Intelligent Water Drops (IWD) algorithm is augmented with a mutation-based local search to find the optimal values of numerical functions. The proposed algorithm called the IWD-CO (IWD for continuous optimization) is tested with six different benchmark functions. The experimental results are satisfactory, which encourage further researches in this regard. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the 4th International Conference of Cognitive Science