Fruit Fly Optimization Algorithm Based on Chaotic Inerrupt

LI Zong-yue; CHEN Zhi-jun; LI Ming-yuan

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Fruit Fly Optimization Algorithm Based on Chaotic Inerrupt

更新时间：2026-09-04

- Fruit Fly Optimization Algorithm Based on Chaotic Inerrupt
- Vol. 33, Issue 7, Pages: 64-68(2016)
- 作者机构：
  
  1. 新疆大学电气工程学院,新疆,乌鲁木齐,830047
  2. 遵义市国家税务局,贵州,遵义,563000
- 作者简介：
- 基金信息：
- DOI：
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- Published：2016
- 稿件说明：
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李宗岳, 陈志军, 李名远. 基于混沌扰动策略的果蝇优化算法[J]. 微电子学与计算机, 2016, 33(7): 64-68.

LI Zong-yue, CHEN Zhi-jun, LI Ming-yuan. Fruit Fly Optimization Algorithm Based on Chaotic Inerrupt[J]. 2016, 33(7): 64-68.
李宗岳, 陈志军, 李名远. 基于混沌扰动策略的果蝇优化算法[J]. 微电子学与计算机, 2016, 33(7): 64-68. DOI：

LI Zong-yue, CHEN Zhi-jun, LI Ming-yuan. Fruit Fly Optimization Algorithm Based on Chaotic Inerrupt[J]. 2016, 33(7): 64-68. DOI：

摘要

果蝇优化算法是模拟果蝇觅食的一种解决优化问题的智能算法

但是为了避免其在优化过程中容易陷入局部极值的缺陷

提出一种新的基于混沌扰动的果蝇优化算法.在迭代过程中

首先利用基本果蝇算法获得最优个体

然后对最优个体引入混沌扰动策略

增强获得全局最优解的可能性.同时通过动态变化系数η调整在迭代寻求过程中混沌扰动变量的值

提高算法跳出局部最优和寻找全局最优的能力.对6个经典测试函数的仿真结果表明

新算法的收敛速度、收敛精度和鲁棒性方面比基本果蝇优化算法具有明显优势.

Abstract

This paper puts forward a new algorithm based on chaotic inerrupt. Firstly the current optimal individual is gained by standard fruit fly optimization algorithm

then chaotic interrupt is added to the current optimal individual to increase the probability of getting the ultimate global optimum. Meanwhile

the value of chaotic variables in the iterative process is adjusted by dynamic variation coefficientηto enhance the ability to escape from the local optimum and seek the global optimum. Simulation results of six classical test functions show that the novel improved algorithm has obvious advantages on convergence precision

convergence speed and robustness.

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references

王克甫, 薛鹏, 黄全振, 等. 求解旅行商问题的改进果蝇算法[J]. 计算机工程与设计, 2014, 34(8): 2789-2792. DOI: 2789

Pan W T. Using modified fruit fly optimization algorithm to perform the function test and case studies[J]. Connection Science, 2013, 25(2/3): 151-160. DOI: 151

Pan W T. A new fruit fly optimization algorithm: taking the financial distress model as an example[J]. Knowledge-Based Systems, 2012, 26(2): 69-74. DOI: 69

潘文超. 果蝇最佳化演算法—最新演化式计算技术[M]. 台湾: 沧海书局, 2011.

刘成忠, 韩俊英. 基于细菌迁徙的自适应果蝇优化算法[J]. 计算机工程与科学, 2014, 36(4): 690-696. DOI: 690

韩俊英, 刘成忠. 自适应变异的果蝇优化算法[J]. 计算机应用研究, 2013, 30(9): 2641-2644. DOI: 2641

刘志雄, 王雅芬, 张煜. 多种群果蝇优化算法求解自动化仓库拣选作业调度问题[J]. 武汉理工大学学报, 2014, 33(3): 71-77. DOI: 71

韩俊英, 刘成忠. 基于历史认知的果蝇优化算法[J]. 计算机科学与探索, 2014, 8(3): 368-375. DOI: 368

韩俊英, 刘成忠. 自适应混沌果蝇优化算法[J]. 计算机应用, 2013, 33(5): 1313-1316. DOI: 1313

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