将混杂进化算法引入图数据挖掘,定义了基于图的染色体表示与加边变异和减边变异算子。针对子图同构问题,采用了SUBDUE提出的带实例的子结构的概念并提出了个体的潜力和带历史的个体两个概念,前者用以衡量一个个体生成新子结构的能力,后者用来保存进化过程中有潜力的个体,从而使减边变异成为可能,在一定程度上克服了子图同构问题。实验结果表明,以上措施增强了算法的寻优能力,提高了算法的效率和解的质量。 The hybrid evolutionary algorithm is introduced into graph data mining, and the graph-based chromosome representation and additive edge mutation and edge deletion mutation operator are defined. For the problem of subgraph isomorphism, the concept of substructure with instance proposed by SUBDUE is adopted and two concepts of individual potential and historical individual are proposed. The former is used to measure the ability of an individual to generate a new substructure. The latter uses To save potential individuals in the process of evolution, thus making it possible to reduce edge variation, to a certain extent, overcome the problem of isomorphism of subgraphs. The experimental results show that the above measures enhance the searching ability of the algorithm and improve the efficiency of the algorithm and the quality of the solution.