Shuffled fruit fly optimization algorithm with local deep search

doi:10.11772/j.issn.1001-9081.2014.04.1060

Journal of Computer Applications ›› 2014, Vol. 34 ›› Issue (4): 1060-1064.DOI: 10.11772/j.issn.1001-9081.2014.04.1060

• Artificial intelligence • Previous Articles Next Articles

Shuffled fruit fly optimization algorithm with local deep search

LIU Chengzhong¹,²,HUANG Gaobao²,ZHANG Renzhi¹,²,CHAI Qiang²

1. College of Resources and Environmental Sciences, Gansu Agricultural University, Lanzhou Gansu 730070, China
2. Gansu Provincial Key Lab of Aridland Crop Science, Lanzhou Gansu 730070, China

Received:2013-10-25 Revised:2013-12-28 Online:2014-04-29 Published:2014-04-01
Contact: ZHANG Renzhi

局部深度搜索的混合果蝇优化算法

刘成忠¹,²,黄高宝²,张仁陟¹,²,柴强²

1. 甘肃农业大学资源与环境学院,兰州 730070
2. 甘肃省干旱生境作物学重点实验室,兰州 730070;

通讯作者: 张仁陟
作者简介:刘成忠(1969-),男,甘肃天祝人,副教授,博士研究生,主要研究方向:智能决策支持系统;
黄高宝(1965-2012),男,甘肃天水人,教授,博士,主要研究方向:农业生态学;
张仁陟(1961-),男,甘肃静宁人,教授,博士,主要研究方向:生态学;
柴强 (1972-),男,甘肃武威人,教授,博士,主要研究方向:农业生态学。
基金资助:
国家自然科学基金资助项目;甘肃省自然科学基金资助项目;甘肃省教育厅科研基金资助项目;甘肃省干旱生境作物学重点实验室开放基金资助项目;甘肃农业大学青年导师基金资助项目

Abstract

Abstract:

In order to overcome the demerits of poor deeply searching ability and easily relapsing into local extremum in basic Fruit Fly Optimization Algorithm (FOA), a new algorithm named Shuffled Fruit Fly Optimization Algorithm with Local Deep Search (SFOALDS) was proposed. The local optimal individual in each group was deeply searched circularly by referencing updating strategy of Shuffled Frog Leaping Algorithm (SFLA). SFOALDS not only efficiently avoids relapsing into local extremum, but also improves convergence velocity and convergence precision in the late evolution. The experimental results show that the proposed algorithm has better global searching performance than basic FOA and SFLA, especially on high dimensional functions.

摘要：

针对基本果蝇优化算法(FOA)局部深度搜索能力较差且易陷入局部最优的缺点，提出了局部深度搜索的混合果蝇优化算法(SFOALDS)。通过借鉴混合蛙跳算法(SFLA)的更新策略，循环进行局部深度搜索操作，使得SFOALDS既保持了FOA较快的收敛速度，又增强了FOA局部深度搜索能力，有效避免了基本FOA易陷入局部最优的缺点，提高了进化后期算法的收敛速度和精度。仿真实验结果表明，SFOALDS比基本FOA和SFLA有较强的全局寻优性能，并且在高维函数上的优势更加明显。

CLC Number:

TP18
TP301.6

LIU Chengzhong HUANG Gaobao ZHANG Renzhi CHAI Qiang. Shuffled fruit fly optimization algorithm with local deep search[J]. Journal of Computer Applications, 2014, 34(4): 1060-1064.

刘成忠黄高宝张仁陟柴强. 局部深度搜索的混合果蝇优化算法[J]. 计算机应用, 2014, 34(4): 1060-1064.

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Shuffled fruit fly optimization algorithm with local deep search

局部深度搜索的混合果蝇优化算法

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