This study aims to investigate the effectiveness of quantum particle swarm optimization (QPSO) algorithms in solving electromagnetic optimization problems.
An enhanced version of the quantum particle swarm approach is developed to solve electromagnetic optimization problems.
The enhanced QPSO methodology is a competent and strong global optimizer for optimizing electromagnetic devices. Furthermore, the experimental outcomes stated in different case studies validate the worth and effectiveness of the proposed approach, with a fast convergence behavior and high solution quality.
The proposed approach encompasses a novel strategy for determining the mean best position within a swarm. A mutation mechanism is used for a particle with the global best position. In addition, a novel parameter adaptation strategy is imposed to maintain the balance between exploration and exploitation searches.
