Abstract:

Artificial Bee Colony（ABC） algorithm is a newly swarm intelligence optimization algorithm.It has become a powerful tool for solving highly nonlinear multi-peak optimization problems.The results of performances testing using three benchmark functions show that the numbers of evaluation for fitness function of ABC are obviously less than that using particle swarm optimization algorithm.Thus，ABC has better suitability for solving multi-modal optimization problems.Finally，ABC algorithm is applied to the design optimization of gravity dam section.The result shows that the artificial bee colony algorithm is feasible and has the advantages of high efficiency and easy implementation.

Key words: structural opti ization, gravity da , global opti ization, artificial bee colony algorith

摘要： 人工蜂群算法是一种新型的群智能优化算法，对于处理复杂的非线性多峰值优化问题具有很好的适用性。对三种典型测试函数进行性能测试，与粒子群优化算法相比较，人工蜂群算法的适应度函数评价次数明显较少，对求解多峰值优化问题具有较好的适应性，将人工蜂群算法应用于重力坝断面优化设计，研究结果表明，该方法是可行的，具有寻优效率高且易于实现的优点。

关键词: 结构优化, 重力坝, 全局优化, 人工蜂群算法