A New Quantum Rotation Angle of Quantum-Inspired Evolutionary Algorithm for TSP

In this paper, Quantum Rotate Gate is improved, which is the main operation in the Population Update of the traditional Quantum Evolutionary Algorithm. A new rotation angle is defined, preventing the algorithm from easily falling into local optimum state in the middle and late term. Based on the characteristics of TSP, a modified quantum rotate gate is proposed in this paper to adaptively adjust the rotation angle, according to the evolution generations and the adapt to degree of the value to adaptive dynamic adjustment of the rotation angle, resulting a better global search capability. At the same time, in order to prevent the extramalization of the probability amplitudes and falling into local optimal algorithm, this paper adopted the H ε gate on the probability amplitude of the rotation to make the corrective manipulation. The comparative experimental results showed that the algorithm's stability and accuracy have been greatly improved in solving the TSP problem, compared with the conventional quantum evolutionary algorithm.