摘要
蚁群算法目前多用于求解组合优化问题.为了让蚁群算法能求解复杂的边坡稳定性分析问题,对基本蚁群算法的结构形式和蚂蚁转移概率的计算进行了改进.针对蚁群算法在演化过程中存在停滞和过早收敛的现象,引入一种自适应搜索算子,改变蚂蚁的选择机制,提高蚂蚁选择的多样性,并由此构建了一种新的蚁群算法——自适应蚁群算法(AACA).研究了AACA在边坡非圆弧临界滑动面搜索中的应用,所给出的算例结果表明:与基本蚁群算法相比,可有效地防止停滞和过早收敛现象,并总能搜索到问题的全局最优解,且搜索效率也有较大的提高.
For ant colony algorithm (ACA) being fit to solve the stability analysis of complex slopes, the structure of ACA and the transfer probability formula were modified. An adaptive operator was introduced to change the selection mechanism of ants and prevent the phenomena of stagnation and premature convergence. Thus, an ant colony algorithm, called adaptive ant colony algorithm (AACA), was presented. Its application to searching for the noncircular critical slip surface of slopes was studied. Several examples were given to test the proposed method. The results show that it can exactly find out the global optimal solution and the search efficiency is higher than that of simple ant colony algorithm.
出处
《浙江大学学报（工学版）》
EI
CAS
CSCD
北大核心
2003年第5期566-569,共4页
Journal of Zhejiang University：Engineering Science
基金
湖南省科技攻关资助项目(02GKY3024).
