期刊
MATHEMATICS AND COMPUTERS IN SIMULATION
卷 174, 期 -, 页码 76-101出版社
ELSEVIER
DOI: 10.1016/j.matcom.2020.02.020
关键词
Firefly algorithm; Adaptive step size; Gaussian distribution; Speed reducer; Three-bar truss
类别
资金
- Science & Technology Program of Henan Province, China [182102310886, 162102110109]
- Postgraduate Education Innovation and Quality Improvement Project of Henan University [SYL18020105, SYL18060145]
This paper proposes a dynamic adaptive firefly algorithm to overcome the disadvantages of the standard firefly algorithm, to improve the convergence rate and solution precision, and to avoid the premature algorithm trapping at the local extreme. It has a global-oriented moving mechanism and can dynamically adjust the step size and attractiveness. First, through the adaptive deviation degree strategy of optimal distance combining with the Gaussian distribution, it optimizes the fixed step-factor to balance the exploration and excavation capabilities of the algorithm and improves the diversity of the population. Second, minimum attractiveness is introduced to the algorithm, and is adaptively changed with the number of iterations, which can avoid random walk due to lack of traction between fireflies. Finally, this paper improves the mobility mechanism based on the position of the current optimal firefly. It enables firefly move with global orientation and also expands the sharing of information between fireflies to improve the overall evolutionary optimization performance of the algorithm. Theoretical analysis proves the convergence and time complexity of the improved algorithm. The simulation results of several test functions and engineering constraint optimization problems show that the improved algorithm has better solution performance, and clearly improves the convergence speed and solution accuracy. (C) 2020 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.
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