Abstract

In the traditional quantum genetic algorithm, the rotation angle and direction of the quantum rotation gate should be looked up from the lookup table which has been designed according to the specific problem. However, this way to solve optimization problems has strong pertinence and poor efficiency so as to miss the global optimal value. For overcome this drawback, the rotation angle and the direction of the quantum rotation gate is determined with the differential evolution algorithm instead, which is a high-efficiency and adaptable evolutionary algorithm. The improved algorithm is applied to solve the function optimization problem, and the numerical results indicate that the improved algorithm has more efficiency and the stronger global optimal capacity. The improved algorithm can be used to optimize the rolling schedule of the tandem cold rolling mills, and the experiment demonstrates that the quantum genetic algorithm based on the differential evolution algorithm is an effective and feasible intelligence method for rolling schedule optimization.

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