新型智能仿生模型——蚁群模型

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Title:

The intelligent bionic model——ant colony

文章编号:

1673-4785(2008)03-0270-09

作者:

高玮;

武汉工业学院土木工程系; 湖北武汉;

Author(s):

GAO Wei

Department of Civil Engineering; Wuhan Polytechnic University; Wuhan 430023; China

关键词:

智能仿生模型;  蚁群模型;  学科交叉;  生物原理

Keywords:

intelligent bionic model;  ant colony model;  subjects intersection;  biological principles

分类号:

Q811.21

文献标志码:

A

摘要:

智能仿生模型是一种多学科交叉的产物,其发展对很多相关学科的发展具有极大的促进作用.蚁群模型是模拟自然界蚁群系统行为而提出的一种新型智能仿生模型,其研究在短短的10余年时间里得到了飞速发展,已成为很多学科的研究热点.我国在这方面的研究尚没有全面开展,为此从仿生原理及实现途径入手,对蚁群模型的几大模型算法进行了详细介绍,并对模型的发展进行了展望.其次,对蚁群模型的典型应用进行了说明,并对模型的最新应用进行了介绍.最后,通过对其他几种仿生算法的介绍,进行了蚁群算法同粒子群算法、免疫算法及进化算法等的比较研究,指出它们的相同点和差异之处.通过对蚁群模型的全面的介绍,以期促进该模型在我国的发展.

Abstract:

Imp roving the intelligent bionic ant colonymodelwill require multidiscip linary research, and so its devel2 opmentwill p romote p rogress in related subjects. The ant colonymodel, a new intelligent bionic modelwhich mim2 ics the behavior of an ant colony, has p rogressed substantially in the last ten years. However, there has been no systematic study of this field in China. To encourage more research this paper gives a detailed introduction to sever2 almajor ant colonymodels according to their underlying bionic p rincip les and simulation methods. The latest devel2 opments in this field are also described. Then, typ ical app lications of ant colonymodels are summarized, and new areaswhere they can be used are p resented. Finally, comparisons are made between the ant colony algorithm, the particle swarm op timization algorithm, the immune algorithm, and the evolutionary algorithm. The similarities and differences between these algorithms are pointed out. This comp rehensive introduction should p romote research on ant colony algorithms in China.