采用基于群智能的模拟退火算法优化起重机箱形梁

Optimization of crane box girder by simulated annealing algorithm based on Swarm Intelligence

详细论述了传统模拟退火算法的基本原理及求解过程,针对算法中存在的缺陷,提出了一种基于群智能的改进方案,采用种群搜索方式进行基于模拟退火的优化设计,提高了算法搜索迭代计算效率;采用Matlab编程软件,在算法运行过程中添加一个数据存储器,用以记录当前最优计算结果,保证全局极值点的准确输出;采用经典的起重机箱形梁优化模型,对改进后的算法进行测试。优化结果表明,改进后的模拟退火算法不仅能克服传统算法效率低的缺点,还具有高效的优化计算能力,为机械结构的优化设计提供了一种高效可行的新方案。

The paper details the basic principle and solving process of the traditional simulated annealing algorithm, and puts forward an improved solution based on swarm intelligence in view of the deficiency in the algorithm. Optimal design based on the simulated annealing is performed using swarm search, which can improve the search iterative calculation effi- ciency; by MATLAB programming soi^ware, a data storage unit is added to the algorithm operating process, to record the current optimal calculation result and maintain accurate output of global extreme points; the classical optimal model for the box girder of the crane is used to test the improved algorithm. The optimized result shows that the improved simulated annealing algorithm can not only overcome the shortcoming of low efficiency of the traditional algorithm, but also possess high-ef- ficient optimal calculation capacity, providing a high-efficient feasible solution for optimal＇design of the mechanical structure.