Improved Differential Evolution on Optimizing 2-Level Ant Clustering Using of Variation

Ant based Clustering (ANT) is a very powerful tool for automatic detection of relevant clusters. The extended version of ANT, two-level Ant based Clustering (2LANT) was introduced for improving ANT clustering in explorative manner. However, structural methods for efficiently confirming the competent optimization of 2LANT initialization are lacking. Due to the important advantages over other optimization algorithms belonging to differential evolution (DE) approach, this paper investigates the utilization of the original DE as well as the variations, here called VarDE1 and VarDE2 as tools for optimizing the initial cluster weights of 2LANT. Such investigated approaches are respectively so called DE+2LANT, VarDE1+2LANT and VarDE2+2LANT. With respect to the different choices of mutation process, both variant DEs would get better accuracy than the original one. More elitism on mutation process is involved with VarDE2+2LANT rather than with VarDE1+2LANT; whilst the most random mutation is applied by DE+2LANT. 10fold cross validation experiments are taken on real-world and artificial data sets with an identified number of clusters. Within the scope of this paper, the investigation results point out the better clustering performance of the variant DEs, VarDE2+2LANT over the related approaches. 