Improved artificial fish swarm algorithm with swine fish

HUANG Bo-ru; FAN Xiao-guang; ZHUO Zhen-fu; HUANG Lei; YANG Yong-jian; LI Xiao-hui

doi:10.13873/J.1000-9787(2015)05-0119-04

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Improved artificial fish swarm algorithm with swine fish

更新时间：2025-09-11

- Improved artificial fish swarm algorithm with swine fish
- Vol. 34, Issue 5, Pages: 119-122(2015)
- 作者机构：
  
  1. 空军工程大学航空航天工程学院
  2. 济南空军航空中心修理厂
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2015)05-0119-04
  CLC： TP18
- Published：2015
- 稿件说明：
移动端阅览
[1]黄柏儒,樊晓光,禚真福,黄雷,杨永建,李晓辉.引入贪心鱼群的改进人工鱼群算法[J].传感器与微系统,2015,34(05):119-122.

HUANG Bo-ru, FAN Xiao-guang, ZHUO Zhen-fu, et al. Improved artificial fish swarm algorithm with swine fish[J]. 2015, 34(5): 119-122.
[1]黄柏儒,樊晓光,禚真福,黄雷,杨永建,李晓辉.引入贪心鱼群的改进人工鱼群算法[J].传感器与微系统,2015,34(05):119-122. DOI： 10.13873/J.1000-9787(2015)05-0119-04.

HUANG Bo-ru, FAN Xiao-guang, ZHUO Zhen-fu, et al. Improved artificial fish swarm algorithm with swine fish[J]. 2015, 34(5): 119-122. DOI： 10.13873/J.1000-9787(2015)05-0119-04.

摘要

针对人工鱼群算法（AFSA）局部寻优不精确等问题

提出一种引入贪心鱼群改进人工鱼群算法（IAFSASF）的方法。贪心鱼群具有不同于普通鱼群的行为策略

在觅食行为中贪心鱼群紧紧跟随在最优适应度的人工鱼的附近进行食物搜索

而不执行追尾和聚群行为

因此

贪心鱼群具有更好的局部寻优能力。实验证明:IAFSASF比原有算法在减少时间复杂度的同时有效提高了求解精度。

Abstract

Aiming at problem of inaccuracy of local search artificial fish swarm algorithm（ AFSA） has

an improved artificial fish swarm algorithm with swine fish（ IAFSASF） is presented. The behavior of the swine fish is different from the normal fish

they always follow artificial fish who has the optimal fitness to search food in the prey and do not execute the follow and swarm

so that the swine fish have better local search ability. The experiment results show that compared with the former algorithm

the IAFSASF reduces time-complexity as well as improves solving precision.

关键词

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references

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