Opposition based particle swarm optimizer with ring topology

Abstract

Particle Swarm Optimizer is population based global search algorithm mimicking the behavior of fish–schooling, bird’s flocking etc. Recently the opposition based learning scheme is incorporated in Particle Swarm Optimizer to improve its performance. Till now opposition based Particle Swarm Optimizer is implemented with gbest topology. This paper proposes the opposition based Particle Swarm Optimizer with lbest or ring topology. The proposed method is applied on 20 benchmark unconstrained functions. The obtained results are compared with other well–known opposition based Particle Swarm Optimizers with statistical analysis. The experimental results with statistical analysis show that the proposed algorithm outperforms over other algorithms for most of the functions.