Improved mayfly optimization algorithm by adaptive random opposition-based learning
Hengqi Zhang, Yong Lin, qian Qian, Jiawen Pan, Yong Feng, Yunfa Fu · 6th International Conference on Mechatronics and Intelligent Robotics (ICMIR2022) · 2022
An adaptive random reverse learning mayfly algorithm is proposed to overcome the shortcomings of mayfly optimization. Specifically, hyperbolic tangent function is used as adaptive curve to flexibly optimize the personal experience and social experience coefficients of the algorithm, so that the algorithm can better balance the global and local search capabilities through the evolutionary iterations. In addition, on the basis of elite mayfly in each generation, random reverse learning mechanism is used to expand population diversity and speed up algorithm convergency. The calculation results of several test functions show that the algorithm presented has good convergence accuracy and improved algorithm performance.