Cluster Occurrence in the DbL_SHADE Population

This paper deals with the Success-History based Adaptive Differential Evolution with Linear decrease in population size and Distance based adaptation of control parameters (DbL_SHADE). The algorithm is subject to the analysis of the population clustering via Density-Based Spatial Clustering of Applications with Noise (DBSCAN). The CEC2015 benchmark set in three dimensional settings (10D, 30D and 50D) was used as a testbed for comparison of the population clustering between L-SHADE and DbL_SHADE algorithms and the results are reported and discussed.