Study of applications of meeting ant colony algorithm to search non-circular critical slip surface of slope

GAO Wei; ZHANG Fei-jun

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Study of applications of meeting ant colony algorithm to search non-circular critical slip surface of slope

更新时间：2026-06-25

- Study of applications of meeting ant colony algorithm to search non-circular critical slip surface of slope
- Vol. 35, Issue S1, (2014)
- 作者机构：
  
  1. 河海大学土木与交通学院,南京,210098
  2. 武汉建工（集团）有限公司,武汉,430023
- 作者简介：
- 基金信息：
- DOI：
  CLC： TU473
- Online First：20 June 2014，
  
  Published：2014
- 稿件说明：
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GAO Wei, ZHANG Fei-jun. Study of applications of meeting ant colony algorithm to search non-circular critical slip surface of slope[J]. 2014, 35(S1).
DOI：

GAO Wei, ZHANG Fei-jun. Study of applications of meeting ant colony algorithm to search non-circular critical slip surface of slope[J]. 2014, 35(S1). DOI：

摘要

边坡非圆弧临界滑动面搜索是边坡稳定计算中的一个关键问题，其实质为安全系数最小的滑动路径搜索问题，采用效果良好的路径搜索算法——蚁群算法是目前研究的热点。为了克服传统蚁群算法效率低、效果差的缺点，基于蚂蚁正反向搜索相遇形成完整路径的原理，提出了一种相遇蚁群算法。将该算法用于边坡非圆弧滑动面搜索问题，提出了一种非圆弧临界滑动面搜索的新方法。通过2个边坡的算例计算及一个水库岸坡的工程应用，验证了新算法的有效性。计算结果表明，相遇蚁群算法无论是整个搜索范围还是从某一点起的搜索范围都要比一般蚁群算法大，所以相遇蚁群算法在搜索边坡临界滑动面时所得到解的多样性也要比一般蚁群算法好，因此，相遇蚁群算法的搜索范围能以较大的概率包含全局最优解，算法最终也能以较大概率搜索到全局最优解。最终，相遇蚁群算法可以在更大的范围内以更快的速度找到边坡的临界滑动面。

Abstract

The search of non-circular critical slip surface is a key problem in slope stability analysis. Essentially

this problem is a path search problem; so the ant colony algorithm is a very suitable method to solve this problem. To overcome the shortcomings of traditional ant colony algorithm

from the principle of combing one whole road by forward and reverse search of ants

here a new algorithm

meeting ant colony algorithm

is proposed. And then this meeting ant colony algorithm is used to locate the critical slip surface of slopes. Through two typical examples and an engineering application of a reservoir bank slope

the effectiveness of the new algorithm is verified. The results show that

from not only the whole search scope but also one point search scope

the meeting ant colony algorithm are all better than traditional ant colony algorithm; so the solutions diversity to search the critical slip surface of slopes by meeting ant colony algorithm is better. And then

to meeting ant colony algorithm

the global optimal solution can be included in the search scope by the larger probability; and the global optimal solution can be obtained by the larger probability. At last

by meeting ant colony algorithm

the critical slip surface of slopes can be found on larger scope and by larger speed.

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