Research Area:  Metaheuristic Computing

Abstract:

In this paper, we propose a reptile search algorithm based on Lévy flight and interactive crossover strategy (LICRSA), and the improved algorithm is employed to improve the problems of poor convergence accuracy and slow iteration speed of the reptile search algorithm. First, the proposed algorithm increases the variety and flexibility of the people by introducing the Lévy flight strategy to prevent premature convergence and improve the robustness of the population. Secondly, an iteration-based interactive crossover strategy is proposed, inspired by the crossover operator and the difference operator. This strategy is applied to the reptile search algorithm (RSA), and the convergence accuracy of the algorithm is significantly improved. Finally, the improved algorithm is extensively tested using 2 test sets: 23 benchmark test functions and 10 CEC2020 functions, and 5 complex mechanical engineering optimization problems. The numerical results show that LICRSA outperforms RSA in 15 (65%) and 10 (100%) of the 2 test sets, respectively. In addition, LICRSA performs best in 10 (43%) and 4 (40%) among all algorithms. Meanwhile, the enhanced algorithm shows superiority and stability in handling engineering optimization.

Keywords:  
reptile search algorithm
Lévy flight
interactive crossover strategy
benchmark
engineering optimization

Author(s) Name:  Liqiong Huang, Yuanyuan Wang , Yuxuan Guo and Gang Hu

Publisher name:  MDPI

DOI:  10.3390/math10132329

Volume Information:  Volume 10 Issue 13

Paper Link:   https://www.mdpi.com/2227-7390/10/13/2329