多目标群搜索优化算法及其在结构设计中的应用

A multi-objective group search optimizer and its application in structural optimal design

为克服工程结构多目标优化设计中遇到的边界处理困难、编程复杂、计算效率低等问题,结合Pareto最优解理论,将群搜索算法改进成多目标群搜索算法(multi-objective group search optimization,MGSO)。通过平面10杆桁架的连续变量优化及空间25杆桁架的离散优化设计的算例,证明多目标群搜索算法在工程结构优化设计中的可行性与实用性。结果表明:多目标群搜索算法作为一种随机算法,其收敛速度快,在计算过程中只需要选择整体最优个体,不需要逐个检查约束,能节省大量的计算时间,对于高维问题,特别是复杂的工程实际问题,有明显的优越性。

There are some problems in the multi-objective optimization of engineering structures, such as the difficulties in dealing with the constraints, the complexity of programming and the low computational efficiency. To solve these problems, an improved group search optimizer combined with Pareto solutions theory was presented. Two examples, including a lO-bar planar truss structure with continuous variables and a 25-bar space truss structure with discrete variables, were employed to evaluate the performance of MGSO. The results showed the feasibility, practicality and superiority of MGSO in structure optimal design. As a stochastic algorithm, MGSO had excellent performance in terms of convergence rate. Only the best individual was needed to be selected and partial constraints were needed to be checked to find the producer, thus a great deal of computational time was saved with MGSO. The MGSO is of obvious advantages for complex engineering problems, especially the high-dimensional ones.