Double Adaptive Artificial Fish Swarm Optimization Algorithm

XU Jian-bo; DAI Yue-ming; YAN Da-hu

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Double Adaptive Artificial Fish Swarm Optimization Algorithm

更新时间：2026-09-04

- Double Adaptive Artificial Fish Swarm Optimization Algorithm
- Vol. 35, Issue 4, Pages: 53-57(2018)
- 作者机构：
  
  1. 江南大学物联网工程学院,江苏,无锡,214122
  2. 江南大学人文学院,江苏,无锡,214122
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2018
- 稿件说明：
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徐建波, 戴月明, 严大虎. 双自适应人工鱼群优化算法[J]. 微电子学与计算机, 2018, 35(4): 53-57.

XU Jian-bo, DAI Yue-ming, YAN Da-hu. Double Adaptive Artificial Fish Swarm Optimization Algorithm[J]. 2018, 35(4): 53-57.
徐建波, 戴月明, 严大虎. 双自适应人工鱼群优化算法[J]. 微电子学与计算机, 2018, 35(4): 53-57. DOI：

XU Jian-bo, DAI Yue-ming, YAN Da-hu. Double Adaptive Artificial Fish Swarm Optimization Algorithm[J]. 2018, 35(4): 53-57. DOI：

摘要

针对人工鱼群算法在函数优化中存在易陷入局部最优、后期收敛速度过慢及寻优精度低等问题

提出了双自适应人工鱼群优化算法.该算法结合基于冯诺依曼拓扑结构的高斯变异自适应人工鱼群算法和引入惯性权重的自适应人工鱼群算法

在相同的自适应调整视野和步长方法下进行迭代寻优.同时引入人工鱼群交流机制

更好地平衡了全局搜索与局部搜索之间的关系.仿真实验表明

该算法有效地提高了寻优质量并且避免了人工鱼群出现早熟的现象.

Abstract

The Artificial Fish Swarm Algorithm has some disadvantages such as falling into local optimum easily

slow convergence rate and low search accuracy. To solve these problems

this paper proposed a double adaptive artificial fish swarm optimization algorithm. Combining gauss mutation adaptive artificial fish swarm algorithm based on Von-neumann neighborhood and an adaptive artificial fish swarm algorithm with inertial weight

the algorithm uses same way that adapt visual and step adaptively to find the optimal solution. At the same time

the artificial fish swarm communication mechanism is introduced. This approach can keep balance between global exploration and local exploration. The simulation results show that the algorithm can effectively improve the quality of the search and avoid the phenomenon of precocious fish.

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references

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