article · 2014
A novel complex-valued bat algorithm
Liangliang LiYongquan Zhou, Springer-Verlag London
Cited by 0Abstract and details only
Abstract
Bat algorithm is a recent optimization algo- rithm with quick convergence, but its population diversity can be limited in some applications. This paper presents a new bat algorithm based on complex-valued encoding where the real part and the imaginary part will be updated separately. This approach can increase the diversity of the population and expands the dimensions for denoting. The simulation results of fourteen benchmark test functions show that the proposed algorithm is effective and feasible. Compared to the real-valued bat algorithm or particle swarm optimization, the proposed algorithm can get high precision and can almost reach the theoretical value.
Cite this paper
Zhou, L. L., & London, S.-V. (2014). A novel complex-valued bat algorithm.
Zhou, Liangliang LiYongquan, and Springer-Verlag London. “A novel complex-valued bat algorithm.” 2014.
Zhou, Liangliang LiYongquan, and Springer-Verlag London. 2014. “A novel complex-valued bat algorithm.”
Zhou, L.L. and London, S.-V. (2014) ‘A novel complex-valued bat algorithm’.
@article{zhou2014novel,
title = {{A novel complex-valued bat algorithm}},
author = {Zhou, Liangliang LiYongquan and London, Springer-Verlag},
year = {2014}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.