Network Based Linear Population Size Reduction in SHADE
Adam Viktorin, Michal Pluháček, Roman Šenkeřík · 2016
This research paper presents a new approach to population size reduction in Success-History based Adaptive Differential Evolution (SHADE). The current L-SHADE algorithm uses fitness function value to select individuals which will be deleted from the current population. Algorithm variant proposed in this paper (Net L-SHADE) is using the information from evolutionary process to construct a network of individuals and the ones which would be deleted are selected based on their degree of centrality. The proposed technique is compared to state-of-art L-SHADE on CEC2015 benchmark set and the results are reported.