Adaptation of Population Structure in Socio-cognitive Particle Swarm Optimization

In the paper a modification of a Socio-cognitive Particle Swarm Optimization algorithm, recently proposed by the authors, is presented. This modification consists in devising a mechanism for dynamic adaptation of the population structure of the swarm. Besides the design and rationale for the approach, referring to the state-of-the-art PSO original algorithm and several of its modifications, experimental results tackling popular benchmark functions are presented and discussed in detail.