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An Adaptive Fruit Fly Optimization Algorithm Based on Velocity Variable
보안공학연구지원센터(IJHIT) International Journal of Hybrid Information Technology Vol.8 No.3 2015.03 pp.329-338
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
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.
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