Analysis on the Convergence of Quantum-inspired Evolutionary Algorithms
نویسندگان
چکیده
This article deals with the convergence of quantum-inspired evolutionary algorithms with one quantum individual and multiple observations. Applying the theory and analytical techniques in non-homogeneous Markov chain, we obtain the conclusion that quantuminspired evolutionary algorithms could converge in probability under some mild conditions imposed on the probability amplitude of the Q-bit individual. We also analyze three cases from both theoretical and experimental viewpoints. The QEA with rotation gate can not guarantee convergence in theory, while others with modified Q-gates meet the convergence conditions. Numerical results further illustrate feasibleness and effectiveness of the improved algorithms.
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