Author(s)

Liu Kaiyuan, Xie Dongqing

Corresponding Author

Liu Kaiyuan

ABSTRACT

In order to solve the shortcomings of Fruit Fly Optimization Algorithm (FOA), which is slow and easy to fall into local optimum, can not specify the domain, Fruit Fly Optimization Algorithm and logstic function transformation are combined to propose an adaptive step improved fruit fly optimization algorithm with logistic transform (ASFOALT). The algorithm improves the correctness of the optimal solution range by improving the fitness function of the FOA, and improves the overall performance of the algorithm by adding the adaptive step mechanism. The experimental results show that ASFOALT has a large improvement in global search capability, convergence speed, convergence accuracy and reliability.

KEYWORDS

fruit fly optimization algorithm, self-adaptive step length.