# Differential evolution algorithm based on wavelet basis function and optimal mutation strategy and application

## A differential evolution algorithm and wavelet basis function technology, applied in computing, computing models, instruments, etc., can solve problems such as poor optimization ability, complex learning process, lack of learning process, etc., to improve algorithm performance, fast convergence speed, strong The effect of optimization

Pending Publication Date: 2019-11-29

CIVIL AVIATION UNIV OF CHINA

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## Abstract

The invention relates to the technical field of differential evolution algorithms and particularly relates to a differential evolution algorithm based on a wavelet basis function and an optimal mutation strategy and application. In the differential evolution algorithm based on the wavelet basis function and the optimal mutation strategy, the wavelet basis function is adopted to control a parameterF and normal distribution to control CR, so that the diversity of solutions is guaranteed. The algorithm convergence is accelerated, and algorithm performance is improved. Upon the selection of mutation policies, advantages are complemented based on five variation strategies. An optimal variation strategy method is provided. The method is used as a variation strategy of a differential evolution algorithm, and is used for improving the local search capability of the algorithm and ensuring the global search characteristic of the algorithm. Meanwhile, the method can efficiently complete effective solution of a test function and an airport gate position allocation problem, and experimental results also prove that the proposed method has competitiveness compared with a comparison method.

Application Domain

Artificial life

Technology Topic

Differential evolutionStrategy method +5

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