Dynamic perturbation for population diversity management in differential evolution

Abstract

The performance of Differential Evolution (DE) is closely related to the population diversity since its mechanism of generating offspring depends wholly on the differences between individuals. This paper presents a simple perturbation technique to maintain the population diversity in which the noise intensity is adjusted dynamically during the search. A modification of the well-known L-SHADE adaptation method is also introduced to manipulate the convergence behaviour of DE. By incorporating these techniques, we develop a new variant of DE called S-LSHADE-DP. Experiment results conducted on the benchmark suite of CEC '22 competition show that S-LSHADE-DP is highly competitive with current state-of-the-art DE-based algorithms. The implementation of S-LSHADE-DP is available at https://github.com/cuonglvsoict/S-LSHADE-DP.