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A Novel Bat Algorithm Based on Differential Operator and Lévy Flights Trajectory
Author(s) -
Jian Xie,
Yongquan Zhou,
Huan Chen
Publication year - 2013
Publication title -
computational intelligence and neuroscience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.605
H-Index - 52
eISSN - 1687-5273
pISSN - 1687-5265
DOI - 10.1155/2013/453812
Subject(s) - trajectory , computer science , operator (biology) , algorithm , differential (mechanical device) , artificial intelligence , physics , biology , thermodynamics , biochemistry , repressor , astronomy , transcription factor , gene
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.

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