Convergence analysis on a class of quantum-inspired evolutionary algorithms

In this article we focus on the theoretical analysis of quantum-inspired evolutionary algorithms with H e gate. Applying the theory and analytical techniques in non-homogeneous Markov chains, we obtain the conclusion that quantum-inspired evolutionary algorithms converge in probability under some mild conditions. Moreover, we estimate the convergence rate relating to parameters of algorithms.