蜂群算法在离散变量结构优化设计中的应用

Application of Bee Colony Algorithm in Structural Optimization Design with Discrete Variables

基于二进制编码将设计变量与其离散取值进行空间映射,随机产生个体并形成初始群体,采取基因突变方法在其邻域范围内产生新食物源,构建了适用于求解离散变量结构优化设计问题的改进蜂群算法。以求解多模测试函数极值问题验证了改进蜂群算法的可行性。通过三杆桁架结构优化设计演示了改进蜂群算法在离散变量优化设计中的应用,优化结果与传统结构优化设计结果相比较,表明改进蜂群算法的有效性。运用蜂群算法求解十杆超静定桁架结构优化问题,计算结果表明改进蜂群算法求解离散变量结构优化问题是可行、有效的。

This paper presents a modified bee colony algorithm for the structural optimization design with discrete variables, which the encoding string and the discrete value are mapped, and a new neighboring food source is produced by mutation of individuals which depends on the fitness value. The performance of the modified bee colony algorithm is tested on the benchmark functions and compared with the basic bee colony algorithm; the experimental results indicate that the modified bee colony algorithm is effective. The application of modified bee algorithm in optimization design of structures with discrete variables is presented with an example of optimization design for three-bar hyper static truss structures with discrete variables. The comparison between the result obtained by traditional method and that by modified bee colony algorithm indicates that the latter is more effective for structural optimization with discrete variables. Modified bee colony algorithm is also used to solve a ten-bar truss structure with discrete variables. The result obtained by modified bee colony algorithm indicates that algorithm is effective and feasible on the structural optimization with discrete variables.