Real-coded quantum evolutionary algorithm based on allele

A real-coded quantum evolutionary algorithm based on allele is presented in order to improve the premature problem and increase the searching accuracy and convergence speed of quantum evolutionary algorithm. In the proposed algorithm, the real variables are encoded according to allele with probability superposition. A hybrid updating strategy is adopted to perform alterable scale mutation on the allele according to the relative optimal property of the allele; under the precondition of balancing the global search and local search, the searching speed is increased. Then, HΕ gate is introduced to update the probability amplitude corresponding to the allele. Finally, the global convergence is proved with Markov chain. The proposed algorithm was compared with the quantum evolutionary algorithm and the quantum genetic algorithm based on double chain encoding using numerical examples, and the results verify the convergence speed and solution accuracy. The proposed algorithm was applied to the parameter optimization in textile slashing process, good optimization result was achieved. ©, 2015, Science Press. All right reserved.