Open AccessA gravitational search algorithm based on levy flight
Author(s) -
Jing Zhao,
Haidong Zhu,
Yinhua Hu,
Enjun Hu,
Baole Huang,
Tingyu Zhang,
Pan Zhang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1865/4/042006
Subject(s) - convergence (economics) , lévy flight , algorithm , search algorithm , range (aeronautics) , computer science , gravitational search algorithm , mathematical optimization , gravitation , function (biology) , mathematics , particle swarm optimization , physics , engineering , aerospace engineering , random walk , statistics , classical mechanics , economics , economic growth , evolutionary biology , biology
A gravitational search algorithm based on levy flight is proposed to solve the problem that the gravitational search algorithm falls into the local optimal solution. Firstly, the dynamic adjustment strategy of gravitational constant is introduced to increase the diversity of particles and improve the convergence speed and accuracy of the algorithm. Then, on the basis of gravitation search algorithm, levy flight is introduced, and the particle search range is increased by using levy flight search mode combining small step and long stride search, so as to improve the global search capability of the algorithm. Finally, six standard test functions are used for simulation analysis. The results show that the improved algorithm has obvious advantages in both convergence speed and convergence precision, and it is more advantageous in multi-peak function optimization.