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Computational Intelligence and Neuroscience
Volume 2013, Article ID 453812, 13 pages
http://dx.doi.org/10.1155/2013/453812
Research Article

A Novel Bat Algorithm Based on Differential Operator and Lévy Flights Trajectory

1College of Information Science and Engineering, Guangxi University for Nationalities, Nanning, Guangxi 530006, China
2Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis, Guangxi University for Nationalities, Nanning, Guangxi 530006, China

Received 16 August 2012; Accepted 1 February 2013

Academic Editor: Christian W. Dawson

Copyright © 2013 Jian Xie et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Aiming at the phenomenon of slow convergence rate and low accuracy of bat algorithm, a novel bat algorithm based on differential operator and Lévy flights trajectory is proposed. In this paper, a differential operator is introduced to accelerate the convergence speed of proposed algorithm, which is similar to mutation strategy “DE/best/2” in differential algorithm. Lévy flights trajectory can ensure the diversity of the population against premature convergence and make the algorithm effectively jump out of local minima. 14 typical benchmark functions and an instance of nonlinear equations are tested; the simulation results not only show that the proposed algorithm is feasible and effective, but also demonstrate that this proposed algorithm has superior approximation capabilities in high-dimensional space.