Abstract:

When quantum optimization algorithm is applied, the difference of optimization control methods will cause the convergence time of optimization algorithm to be too long. Therefore, a quantum optimization algorithm for decentralized performance of nonlinear chaotic network systems is proposed. The piecewise Logistic chaotic mapping method is used to obtain the quantum initialization position. Based on the fitness division of quantum populations, the corresponding evolutionary models are established for the top and bottom populations respectively. Using multiple nonlinear continuous time subsystems, the nonlinear chaos optimal control method is designed and the optimal control scheme is determined. Finally, the premature convergence judgment mechanism is introduced to obtain the calculation results of the optimal solution. Experimental results show that the convergence time of the proposed optimization algorithm is significantly reduced compared to the traditional method.

Key words: nonlinear chaotic network system, dispersed, quantum optimization, chaos initialization, stagnation, optimal control