Levy Flight Ant Lion Optimizer with Adaptive Boundary and Optimal Guidance

WANG Ruo-an; ZHOU Yue-wen; HAN Bo; LI Jian-feng; LIU Qiang

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Levy Flight Ant Lion Optimizer with Adaptive Boundary and Optimal Guidance

更新时间：2026-09-04

- Levy Flight Ant Lion Optimizer with Adaptive Boundary and Optimal Guidance
- Vol. 35, Issue 9, Pages: 20-25(2018)
- 作者机构：
  
  空军工程大学机构航空航天工程学院,陕西,西安,710038
- 作者简介：
- 基金信息：
- DOI：
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- Published：2018
- 稿件说明：
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王若安, 周越文, 韩博, 李剑峰, 刘强. 具有自适应边界与最优引导的莱维飞行蚁狮优化算法[J]. 微电子学与计算机, 2018, 35(9): 20-25, 31.

WANG Ruo-an, ZHOU Yue-wen, HAN Bo, et al. Levy Flight Ant Lion Optimizer with Adaptive Boundary and Optimal Guidance[J]. 2018, 35(9): 20-25.
王若安, 周越文, 韩博, 李剑峰, 刘强. 具有自适应边界与最优引导的莱维飞行蚁狮优化算法[J]. 微电子学与计算机, 2018, 35(9): 20-25, 31. DOI：

WANG Ruo-an, ZHOU Yue-wen, HAN Bo, et al. Levy Flight Ant Lion Optimizer with Adaptive Boundary and Optimal Guidance[J]. 2018, 35(9): 20-25. DOI：

摘要

针对蚁狮算法存在探索与开发能力不平衡的缺点

提出了具有自适应边界与最优引导的莱维飞行改进算法.首先蚁狮调整边界范围

蚂蚁做莱维飞行

以此平衡探索与开发能力; 其次较差蚁狮做高斯变异

并通过自适应最优引导方程

提高收敛速度和全局搜索能力.6个标准测试函数的仿真结果表明

相比其它算法

提出的改进算法提高了最优解的精度和收敛速度.

Abstract

Aiming at the shortcoming that the ant-lion algorithm has unbalanced exploration and development capability

an improved levy flight algorithm with adaptive boundary and optimal guidance is proposed. First

the ant lion to adjust the scope of the border

ants do levy flight

in order to balance the exploration and development capabilities. Second

the worse Ant lion do Gaussian mutation

and through the adaptive best-guided equation

to improve the convergence speed and global search ability. The simulation results of six standard test functions show that the improved algorithm improves the accuracy and convergence speed of the optimal solution compared with other algorithms.

关键词

Keywords

references

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廖灿星, 张平, 李行善, 等.基于混合人工鱼群算法的传感器网络优化[J].北京航空航天大学学报, 2010, 36(3): 373-377. DOI: 373

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