基于多群智能优化算法的数据库查询优化研究

Research on Database Query Optimization Based on Multi Group Intelligent Optimization Algorithm

查询优化是提高数据库性能的关键技术,针对数据库查询优化效率低的难题,提出了一种多群智能优化算法相融合的数据库查询优化算法。首先按照布谷鸟优化算法对鸟巢位置进行更新,然后利用蝙蝠算法的动态转换策略对鸟巢位置进一步更新,避免算法陷入局部最优,最后通过仿真实验对算法的性能进行测试。结果表明,其算法是解决数据库查询优化的有效途径,能够获得理想的数据库查询计划,具有实际意义。

Query optimization is a key factor to improve the performance of database systems.In order to solve low query problem of traditional database query optimization algorithm,a novel query optimization method of database is proposed based on multi group intelligent optimization algorithm.Firstly,nest location is updated according to the basic cuckoo search optimization algorithm,and then cuckoo nest location is further replaced according to the dynamic conversion strategy in the bat algorithm,avoiding falling into a local optimum.Finally it is applied to solve the query optimization problem of database,and the performance is tested by simulation experiments.The results show that the proposed algorithm is an effective method for database query optimization,and can obtain good query optimization plan.