  Motivated by 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
analysed and compared with the classical PSO. It has been proven that QPSO-CD
handles such real-life problems efficiently and can attain superior solutions
in most of the problems. The experimental results showed that QPSO associated
with Cauchy distribution and natural selection strategy outperforms other
variants in the context of stability and convergence.
