中文摘要：

人工蜂群算法是模仿蜜蜂行为提出的一种群智能优化算法。它的主要特点是只需要对问题的解进行优劣的比较,通过各人工蜂个体的局部寻优行为,最终在群体中使全局最优值突现出来,具有较快的收敛速度,但较容易陷入局部最优解。为了克服这一不足,将模拟退火算法机制引入其中进行改进。既保留了蜂群算法群体寻优的特点,又可以有效地避免陷入局部最优解。通过选择合适的收益率函数和温度下降函数,可以很方便地解决优化问题。通过构造基于残余力向量的损伤识别目标函数,利用改进的人工蜂群算法,能有效地解决结构损伤识别问题。通过对桁架模型进行数值模拟,结果表明文中算法就原算法而言,收敛速度,识别精度和抗噪声能力有较好改善。

英文摘要：

Artificial Bee Colony Algorithm is an optimization method based on simulating the bee＇s behavior. It is a kind of swarm intelligence and used widely for engineering problem. Its main character is just to make the comparison between the solutions,at last acquiring the global optimal solution. Its convergence speed is fast but it is easy to trap into the local optimum. Simulated Annealing process is introduced in the algorithm to overcome the shortage. In the damage identification,an objective function is defined based on the residual force vector,and then the proposed method is used to identify the structural damage. A planar truss is studied as an example to illustrate the correctness and efficiency of the present method. Study shows excellent identified results can be obtained even with noisy measurements. Compared with original algorithm,the modified one has a quicker convergence rate and gets a better result,and it is not sensitive to artificial measurement noise.