QPSO-CD: quantum-behaved particle swarm optimization algorithm with Cauchy distribution

• Published in: Quantum information processing 2020-10, Vol.19 (10), Article 345
• Main Authors: Bhatia, Amandeep Singh, Saggi, Mandeep Kaur, Zheng, Shenggen
• Format: Article
• Language: English
• Subjects: Algorithms; Data Structures and Information Theory; Mathematical Physics; Optimization; Particle swarm optimization; Physics; Physics and Astronomy; Quantum Computing; Quantum Information Technology; Quantum Physics; Spintronics
• ISSN: 1570-0755; 1573-1332
• DOI: 10.1007/s11128-020-02842-y

Motivated by the particle swarm optimization (PSO) and quantum computing theory, we have presented a quantum variant of PSO (QPSO) mutated with Cauchy operator and natural selection mechanism (QPSO-CD) from evolutionary computations. The performance of proposed hybrid quantum-behaved particle swarm optimization with Cauchy distribution (QPSO-CD) is investigated and compared with its counterparts based on a set of benchmark problems. Moreover, QPSO-CD is employed in well-studied constrained engineering problems to investigate its applicability. Further, the correctness and time complexity of QPSO-CD are analyzed and compared with the classical PSO. It has been proved that QPSO-CD handles such real-life problems efficiently and can attain superior solutions in most of the problems. The experimental results shown that QPSO associated with Cauchy distribution and natural selection strategy outperforms other variants in context of stability and convergence.