Applying distance sorting selection in differential evolution

Differential evolution is eligible for solving continuous optimisation problems. So far, the imbalance between exploration and exploitation in DE runs often leads to the failure to obtain good solutions. In this paper, we propose distance sorting selection where the individual has the best fitness among parents and offspring is selected firstly. Then, the genotype distance from another individual to it, which resembles the distance in their chromosome structure, can be estimated to decide whether the former individual is selected. Under the control of an adaptive scheme as proposed in the paper, we use it to replace the original selection of the CoBiDE in runs from time to time. Experimental results show that, for many among the 25 CEC 2005 benchmark functions, which have the similar changing trend of diversity and fitness in runs, our adaptive scheme for calling selection based on distance sorting brings improvement on solutions.