title: A novel bat algorithm based on differential operator and Lévy flights trajectory.
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.
authors.affiliation: College of Information Science and Engineering, Guangxi University for Nationalities, Nanning, Guangxi, China.
authors.forename: Jian
authors.initials: J
authors.lastname: Xie
authors.forename: Yongquan
authors.initials: Y
authors.lastname: Zhou
authors.forename: Huan
authors.initials: H
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D000818:Animals; D019985:Benchmarking; D002685:Chiroptera / Q000502:physiology*; D003627:Data Interpretation, Statistical; D005426:Flight, Animal / Q000502:physiology*; D008959:Models, Neurological; D017711:Nonlinear Dynamics; D015203:Reproducibility of Results; D012984:Software