%0 Journal Article
%T An Improved Bat Algorithm Based on L¨¦vy Flights and Adjustment Factors
%J Symmetry | An Open Access Journal from MDPI
%D 2019
%R https://doi.org/10.3390/sym11070925
%X This paper proposed an improved bat algorithm based on L¨¦vy flights and adjustment factors (LAFBA). Dynamically decreasing inertia weight is added to the velocity update, which effectively balances the global and local search of the algorithm; the search strategy of L¨¦vy flight is added to the position update, so that the algorithm maintains a good population diversity and the global search ability is improved; and the speed adjustment factor is added, which effectively improves the speed and accuracy of the algorithm. The proposed algorithm was then tested using 10 benchmark functions and 2 classical engineering design optimizations. The simulation results show that the LAFBA has stronger optimization performance and higher optimization efficiency than basic bat algorithm and other bio-inspired algorithms. Furthermore, the results of the real-world engineering problems demonstrate the superiority of LAFBA in solving challenging problems with constrained and unknown search spaces. View Full-Tex
%U https://www.mdpi.com/2073-8994/11/7/925