A Particle Swarm Optimization Algorithm Based on Diffusion-Repulsion and Application to Portfolio Selection

Inspired by the diffusion movement phenomenon of the molecules, this paper presents a diffusion-repulsion particle swarm optimization (DRPSO). The proposed new algorithm (DRPSO) includes attraction and repulsion (or migration) phases. Once the diversity of population becomes too low, the individuals will be dispersed and carry out diffusion movement, while if the diversity of population becomes too high, the individuals have to be congregated, which is accomplished by diversity control method. Comparisons with standard SPSO and other algorithms on a portfolio problem indicate that DRPSO not only prevents premature convergence to a high degree, but also keeps a more rapid convergence rate than SPSO.