[1]印 峰,王耀南,刘 炜,等.个体速度差异的蚁群算法设计及仿真[J].智能系统学报,2009,4(06):528-533.[doi:10.3969/j.issn.1673-4785.2009.06.010]
 YIN Feng,WANG Yao-nan,LIU Wei,et al.Design and simulation of an ant colony algorithm based on individual velocity differences[J].CAAI Transactions on Intelligent Systems,2009,4(06):528-533.[doi:10.3969/j.issn.1673-4785.2009.06.010]
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个体速度差异的蚁群算法设计及仿真(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第4卷
期数:
2009年06期
页码:
528-533
栏目:
出版日期:
2009-12-25

文章信息/Info

Title:
Design and simulation of an ant colony algorithm based on individual velocity differences
文章编号:
1673-4785(2009)06-0528-06
作者:
印   峰1王耀南1刘   炜2周   良1
1.湖南大学 电气与信息工程学院,湖南 长沙 410082; 2.湖南科技职业学院 软件学院,湖南 长沙 410118
Author(s):
YIN Feng1 WANG Yao-nan1 LIU Wei2 ZHOU Liang1
1. College of Electrical and Information Engineering of Hunan University, Changsha 410082, China; 2. School of Software, Hunan Vocational College of Science and Technology, Changsha 410118,China
关键词:
蚁群算法旅行商问题信息素NP-难解
Keywords:
ant colony algorithm TSP pheromone NP-hard
分类号:
TP301.6
DOI:
10.3969/j.issn.1673-4785.2009.06.010
文献标志码:
A
摘要:
针对如何提高蚁群算法搜索速度及防止算法停滞问题,提出一种改进的蚁群优化算法VACO(ACO algorithm based on ant velocity),通过构造与局部路径和蚂蚁个体速度相关的时间函数,并建立与时间函数相关的动态信息素释放机制,加快信息素在较优路径上正反馈过程,从而提高了算法的收敛速度;采取一种连续小区间变异策略,在加快局部搜索过程的同时可有效防止算法陷入局部最优.对典型TSP问题的仿真研究结果表明,改进后的算法在收敛性和对较好解的探索性能得到一定程度的提高.
Abstract:
A new implementation of the ant colony optimization (ACO) algorithm was primarily focused on improving search speed and preventing stagnation. To resolve these two issues, improvements based on velocity were proposed, producing a VACO algorithm. By constructing a time-function for local paths and ant velocity, and building a dynamic release mechanism for pheromones in the time-function, it accelerated positive feedback from the accumulation of pheromones, leading to better paths and improved convergence speed. A strategy of continuous inter-cell mutation sped up local searches and at the same time effectively prevented the algorithm being trapped in local optimums. The results showed that the proposed algorithm improves convergence and increases the possibility of finding optimal solutions.

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备注/Memo

备注/Memo:
收稿日期:2009-08-12.
基金项目:国家科技支撑计划资助项目(2008BAF36B01);国家“863”计划资助项目(2008AA04Z214).
作者简介:
印    峰,男,1983年生,博士研究生,主要研究方向为机器人控制及人工智能计算.
王耀南,男,1957年生,教授,博士生导师,主要研究方向为智能机器人、智能信息处理和智能控制.现任湖南大学电气与信息工程学院院长,国家高效磨削工程技术研究中心副主任,教育部输变电新技术工程研究中心主任.国际IEEE高级会员,国际自动控制联IFAC会员,中国人工智能学会、自动化学会、电机工程学会理事.在国内外发表学术论文200多篇,出版专著和教材4部. 
刘   炜,男,1981年生,助教,硕士,主要研究方向为人工智能.
更新日期/Last Update: 2010-02-22