离散变量桁架结构拓扑优化的杂交算法

A Hybrid Algorithm for Topology Optimization of Truss Structures with Discrete Variables

为了加快遗传算法的进化过程,提出了遗传算法和拟满应力算法相结合的杂交算法,并将它应用于离散变量桁架结构的拓扑优化问题·在对桁架结构受力分析的基础上,提出一种启发式方法对随机生成的拓扑结构形式作必要修正,以快速产生符合机动性要求的拓扑结构形式·利用遗传算法进行桁架结构拓扑优化,用拟满应力算法进行截面优化,并将截面优化的结果传递给遗传算法作为拓扑优化中遗传操作的根据,这样大大减少单纯用遗传算法进行优化的解空间,从而加快搜索进程·算例的结果表明,该方法用于桁架结构拓扑优化是简单、快速和有效的·

A hybrid algorithm (HA) integrating the quasi-full stress algorithm and the standard genetic algorithm (SGA) is proposed to expedite the evolving process of genetic algorithm so as to apply it to the topology optimization of truss structures with discrete variables. Based on a force analysis of truss structures, a necessary modification is done in a heuristic way to the topological structure types that form randomly, thus forming rapidly such types to meet the requirement of their adaptabilities. The genetic algorithm is used to optimize the topology of truss structures and the quasi-full stress algorithm used to optimize cross-sections, then the results of cross-section optimization are transferred to genetic algorithm as the basis of genetic operation in topology optimization. The solution space to be optimized simply by genetic algorithm can thus be reduced greatly so as to expedite search process. The exemplification results showed that the method proposed is really simple, fast and efficient to the topology optimization of structures.