Chaos-enhanced multiple-choice strategy for particle swarm optimisation
Michal Pluháček, Roman Šenkeřík, Adam Viktorin, Tomáš Kadavý · International Journal of Parallel Emergent and Distributed Systems · 2018
In this paper, we use pseudo-random number generators based on six chaotic systems to enhance the performance of multiple-choice strategy for particle swarm optimisation (PSO). The multiple-choice strategy is a heterogeneous swarm-based method. We present the results of benchmark testing using the latest CEC’17 benchmark suite. The performance of the proposed method is compared with the canonical PSO and evaluated for statistical significance.Utilising of pseudo-random number generators based on six chaotic systems to enhance the performance of multiple-choice strategy for particle swarm optimization.