[1]陈明杰,黄佰川,张旻.混合改进蚁群算法的函数优化[J].智能系统学报,2012,7(4):370-376.
　CHEN Mingjie,HUANG Baichuan,ZHANG Min.Function optimization based on an improved hybrid ACO[J].CAAI Transactions on Intelligent Systems,2012,7(4):370-376.
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混合改进蚁群算法的函数优化

《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷: 7 期数: 2012年第4期 页码: 370-376 栏目: 学术论文—人工智能基础 出版日期: 2012-08-25
Title:
Function optimization based on an improved hybrid ACO
文章编号:
1673-4785(2012)04-0370-07
作者:
陈明杰，黄佰川，张旻
哈尔滨工程大学 自动化学院，黑龙江 哈尔滨 150001
Author(s):
CHEN Mingjie, HUANG Baichuan, ZHANG Min
College of Automation, Harbin Engineering University, Harbin 150001, China
关键词:
混合改进蚁群算法; 函数优化; 自适应; 高斯变异; 蚁群算法
Keywords:
improved hybrid ant colony optimization;  function optimization;  selfadaptive;  Gaussian mutation; ant colony optimization
分类号:
TP181
文献标志码:
A
摘要:
针对蚁群算法进化速度慢、容易出现停滞现象的不足，探讨了一种基于自适应信息素挥发因子的改进蚁群算法．针对蚁群算法容易陷入局部最优的缺点，提出了一种基于决策变量高斯变异的改进蚁群算法．针对蚁群算法速度慢的不足，探讨了一种基于决策变量边界自调整的改进蚁群算法．将上述3种改进相融合，提出了一种基于自适应信息素挥发因子、决策变量高斯变异和决策变量边界自调整3种改进策略的混合改进蚁群算法．将其应用于函数优化中，仿真结果表明，混合改进蚁群算法在收敛速度和收敛率方面都有很大改进，具有更好的寻优性能．
Abstract:
Considering the low evolution speed and the tendency towards stagnation of ant colony optimization (ACO), an improved ACO was discussed based on an adaptive pheromone evaporation factor. To avoid the defect of ACO easily falling into the local optimum, another improved ACO was proposed based on Gaussian variation of decision variables. To overcome the shortcoming of the slow speed of ACO, a new and improved ACO was given based on boundary selftuning of the decision variables. Finally, an improved hybrid ant colony algorithm was proposed, which combined the adaptive pheromone evaporation factor, Gaussian variation of decision variables, and boundary selftuning of the decision variables. When applied to function optimization, the simulation results show that the improved hybrid ACO has a higher degree of accuracy, a higher convergence ratio, and improved optimization performance.
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备注/Memo

收稿日期：2011-11-11.
网络出版日期：2012-07-12.
基金项目：国家自然科学基金资助项目（51079033）；中央高校基本科研业务费专项资金资助项目（HEUCF100430）.
通信作者：陈明杰.
E_mail：chenmingjie@hrbeu.edu.cn．
作者简介：
陈明杰，女，1977年生，副教授，硕士生导师，博士，主要研究方向为复杂系统的智能控制、图像处理与模式识别等.发表学术论文30余篇，其中11篇被EI/ISTP检索.

更新日期/Last Update: 2012-09-26
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