Abstract:
Since its inception in 1995, many improvements to the original particle swarm
optimization (PSO) algorithm have been developed. This paper reviews one class of such
PSO variations, i.e. PSO algorithms that make use of crossover operators. The review is
supplemented with a more extensive sensitivity analysis of the crossover PSO algorithms
than provided in the original publications. Two adaptations of a parent-centric crossover
PSO algorithm are provided, resulting in improvements with respect to solution accuracy
compared to the original parent-centric PSO algorithms. The paper then provides an extensive
empirical analysis on a large benchmark of minimization problems, with the objective to
identify those crossover PSO algorithms that perform best with respect to accuracy, success
rate, and efficiency.
