Hybrid artificial fish swarm algorithm based on mutation operator

doi:10.3778/j.issn.1002-8331.2009.33.010

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (33): 28-30.DOI: 10.3778/j.issn.1002-8331.2009.33.010

• 研究、探讨 • Previous Articles Next Articles

Hybrid artificial fish swarm algorithm based on mutation operator

HUANG Hua-juan，ZHOU Yong-quan

College of Math. and Computer Science，Guangxi University for Nationalities，Nanning 530006，China

Received:2008-07-03 Revised:2008-10-06 Online:2009-11-21 Published:2009-11-21
Contact: HUANG Hua-juan

基于变异算子的人工鱼群混合算法

黄华娟，周永权

广西民族大学数学与计算机科学学院，南宁 530006

通讯作者: 黄华娟

Abstract

Abstract: A Hybrid Artificial Fish Swarm Algorithm（HAFSA） is proposed，where the Hooke-Jeeves pattern search is combined with AFSA to speed up the local search，also mutation operator is embedded to avoid the common defect of premature convergence.So the hybrid algorithm is capable of improving the local search ability of the algorithm，as well as reducing the computational burden.The experimental results through testing by functions and practical problems show that the hybrid algorithm is efficient and effective.

Key words: artificial fish school algorithm, Hooke-Jeeves method, hybrid algorithm, mutation

摘要： 把Hooke-Jeeves 模式搜索方法作为人工鱼群算法的一个局部搜索算子，嵌入到带变异算子的人工鱼群算法中，提出一种基于变异算子的人工鱼群混合算法。其中，Hooke-Jeeves的强局部搜索能力提高了人工鱼群混合算法的局部收敛速度，变异算子的引入增加了群体的多样性，避免人工鱼群混合算法陷入局部最优。通过基准函数和实例测试验证，表明了该算法是高效可行的。

关键词: 人工鱼群算法, Hooke-Jeeves方法, 混合算法, 变异

CLC Number:

TP18

HUANG Hua-juan，ZHOU Yong-quan. Hybrid artificial fish swarm algorithm based on mutation operator[J]. Computer Engineering and Applications, 2009, 45(33): 28-30.

黄华娟，周永权. 基于变异算子的人工鱼群混合算法[J]. 计算机工程与应用, 2009, 45(33): 28-30.

[1]	ZOU Jie, LI Jun. Multi-strategy Covariance Matrix Learning Differential Evolution Algorithm [J]. Computer Engineering and Applications, 2021, 57(7): 78-87.
[2]	CAI Dongli, ZHONG Qinghua, ZHU Yongsheng, LIAO Jinxiang, HAN Maizhi. EEG Emotion Recognition Using Convolutional Neural Network with 3D Input [J]. Computer Engineering and Applications, 2021, 57(5): 161-167.
[3]	ZHANG Weikang, LIU Sheng, REN Chunhui. Mixed Strategy Improved Sparrow Search Algorithm [J]. Computer Engineering and Applications, 2021, 57(24): 74-82.
[4]	LI Shouyu, HE Qing, DU Nisuo. Piecewise Weight and Mutation Opposition-Based Learning Butterfly Optimization Algorithm [J]. Computer Engineering and Applications, 2021, 57(22): 92-101.
[5]	WEN Zeyu, XIE Jun, XIE Gang, XU Xinying. Multi-objective Sparrow Search Algorithm Based on New Crowding Distance [J]. Computer Engineering and Applications, 2021, 57(22): 102-109.
[6]	REN Chunhui, LIU Sheng, ZHANG Weikang, ZHANG Weiwei. Optimization and Application of Cauchy Mutation Camel Algorithm [J]. Computer Engineering and Applications, 2021, 57(21): 87-94.
[7]	CHEN Lei, YIN Junsheng. Whale Swarm Optimization Algorithm Based on Gaussian Difference Mutation and Logarithmic Inertia Weight [J]. Computer Engineering and Applications, 2021, 57(2): 77-90.
[8]	ZHOU Yuanling, HU Xiaobing, JIANG Daiyu, LI Hang. Research on Optimization Algorithm of Workshop Scheduling Based on Improved NSGA-II [J]. Computer Engineering and Applications, 2021, 57(19): 274-281.
[9]	WAN Da, LI Jun. Fireworks Algorithm Based on Tournament Elite Learning and Covariance Mutation [J]. Computer Engineering and Applications, 2021, 57(19): 84-96.
[10]	HAO Xiang, HE Yichao, ZHU Xiaobin, ZHAI Qinglei. Discrete Hybrid Multi-verse Optimization Algorithm for Solving Discounted {0-1} Knapsack Problem [J]. Computer Engineering and Applications, 2021, 57(18): 103-113.
[11]	WANG Lili, SHEN Yi, XU Yusong, YUAN Mingxin. Clonal Selection Algorithm Combining Cloud Model and Reverse Learning [J]. Computer Engineering and Applications, 2021, 57(17): 68-74.
[12]	WU Weijie, ZHANG Jingxiang. Random Forest Feature Selection Algorithm Based on Categorization Information and Application [J]. Computer Engineering and Applications, 2021, 57(17): 147-156.
[13]	WU Guangfu, CHEN Ying. Summary of Research and Application of Flower Pollination Algorithm [J]. Computer Engineering and Applications, 2021, 57(15): 30-41.
[14]	FENG Xiaodong, HUANG Shirong, DAI Guan’ou, YANG Weijia, LUO Yaozhi. Research and Application of Beetle Antennae Genetic Hybrid Algorithm [J]. Computer Engineering and Applications, 2021, 57(15): 90-100.
[15]	LI Rong, HE Xingshi, YANG Xinshe. Application of Moth Algorithm Based on Differential Evolution in Power Dispatch [J]. Computer Engineering and Applications, 2021, 57(13): 258-268.

Hybrid artificial fish swarm algorithm based on mutation operator

基于变异算子的人工鱼群混合算法

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics