원문정보
초록
영어
In view of the problems of easily relapsing into local extremum and low convergence accuracy of fruit fly optimization algorithm (FOA), this paper proposes a adaptive fruit fly optimization algorithm based on velocity variable (VFOA). The idea of this algorithm is based on the flight characteristics of fruit fly, using particle swarm optimization (PSO) concept of particle velocity, based on fruit fly optimization algorithm, improved the convergence speed of fruit fly optimization algorithm by adding the particle velocity variable parameter. Finally, simulation comparison experiment tests are conducted on 13 benchmark functions, test results show that adaptive fruit fly optimization algorithm based on velocity variable VFOA compared to swarm intelligence algorithms of FOA, PSO, CS, and so on, the convergence speed and accuracy are improved obviously.
목차
1. Introduction
2. Fruit Fly Optimization Algorithm
3. Adaptive Fruit Fly Optimization Algorithm Based on Velocity Variable
4. Experimental Results and Analysis
4.1. Experimental Set Up
4.2. Experiment Parameters Setting
4.3. Algorithm Comparison
4.4. The Higher Dimensional Function Test
5. Conclusions
Acknowledgments
References