摘要
蚁狮优化算法是受自然界中蚁狮捕食蚂蚁的行为提出的群智能优化算法。针对基本蚁狮优化算法存在易陷入局部最优的缺点,论文提出一种基于逻辑自映射和Beta变异的混沌蚁狮优化算法。在基本蚁狮优化算法中引入逻辑自映射混沌序列优化精英个体,使用Beta变异策略对适应度值较差的种群个体进行变异,使得算法能有效跳出局部极值。对Benchmark基准函数的寻优测试表明,改进后的算法与基本蚁狮优化算法和粒子群算法相比,其寻优速率、收敛精度及算法稳定性更佳。
The antlion optimization algorithm is a novel biomimetic group intelligent optimization algorithm derived from the behavior of ant lions preying on ants in nature.Aiming at the shortcomings of the basic antlion optimization algorithm which is easy to fall into local optimum,a chaotic antlion optimization algorithm based on self-logical mapping and Beta mutation is proposed.A series of chaotic variables according to the self-logical mapping function are introduced into the course of ALO to optimize the elite of antlion.Beta mutation strategy is performed on individual populations with poor fitness values,which allows the algorithm has capability to jump out of the local optima.Standard test functions are used for testing and it is proved that the improved antlion algorithm is superior to the ALO algorithm and PSO algorithm in terms of convergence rate,convergence accuracy and stability.
作者
胡元娇
郭玉纯
HU Yuanjiao;GUO Yuchun(School of Computer Science,Xi'an University of Posts and Telecommunications,Xi'an 710121)
出处
《计算机与数字工程》
2020年第7期1611-1616,共6页
Computer & Digital Engineering
关键词
蚁狮优化算法
逻辑自映射
Beta变异
混沌
antlion optimization algorithm
self-logical mapping
Beta mutation
chaotic
