离散变量桁架结构拓扑优化的混合遗传算法

为了避免结构拓扑优化过程中杆件和节点的增删带来的计算上的麻烦，在对桁架结构受力分析的基础上，提出一种启发式方法，以快速产生符合机动性要求的拓扑结构形式；然后在既定的拓扑结构形式下采用混合遗传算法——拟满应力遗传算法进行截面优化。该方法通过在遗传算法中嵌入拟满应力算子，同时对基本遗传算法采用最优个体保留、最差个体替换和控制种群个体差异等改进措施，有效提高遗传算法求解的效率和质量。算例结果表明，该方法用于离散变量桁架结构拓扑优化是有效的。

HYBRID GENETIC ALGORITHM FOR DISCRETE TOPOLOGY OPTIMIZATION OF TRUSSES

A hybrid genetic algorithm (HGA) for discrete topology optimization of trusses is proposed. It composed the standard genetic algorithm (SGA) and the imitative full-stress design method. In order to avoid the calculating trouble of additions and deletions of the unit and the node, on the based of analysis of truss structure, one kind of heuristic means for producing the topology-structure shape which meet the maneuverability demand quickly was proposed. Using hybrid genetic algorithm under the condition of topology-structure shape processed cross-section optimization. Imitative full-stress operator was inserted into genetic algorithm for improving local searching capability of genetic algorithm in this method. Moreover standard genetic algorithm was improved by employing the best individual reserved, the worst individual replaced and difference of individuals controlled, which effectively improved the efficiency and quality of genetic algorithm.The results by exemplification show that HGA was efficient optimal method for truss-structure topology optimization with discrete variables.