A Quantum-Based Particle Swarm Optimization Algorithm Applied to Inverse Problems

Abstract

To balance exploration and exploitation searches in order to prevent premature convergences in Particle Swarm Optimization (PSO) algorithms, an improved Quantum-based PSO (QPSO) algorithm is proposed with an ultimate goal of preserving the simplicities of available QPSOs. The improvements include the design of diversification and intensification phases, searching mechanisms and a strategy to shift away from the worst solutions. The proposed QPSO are compared to available optimizers on two case studies to showcase its merits.