基于BACS算法的数据库查询优化

Database query optimization based on Bat Algorithm and Cuckoo Search Algorithm

针对布谷鸟算法局部搜索能力弱、寻优精度低等缺陷,提出一种蝙蝠算法和布谷鸟算法相融合的数据库查询优化算法(BACS)。按照布谷鸟优化算法对鸟巢位置进行更新,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;最后将BACS应用于数据库查询优化问题求解,并通过仿真实验对BACS的性能进行测试。实验结果表明,BACS加快了数据库查询优化求解的收敛速度,获得了质量更高的查询优化方案。

In order to solve the problems of bat algorithm which has low optimizing accuracy and weak local search ability,a novel query optimization method of database is proposed based on Bat Algorithm and Cuckoo Search Algorithm（BACS）.Firstly,nest location is updated according to the cuckoo search optimization algorithm,and then cuckoo nest location is further replaced according to the dynamic conversion strategy in the bat algorithm and avoids falling into local optimum,finally it is applied to solve the query optimization problem of database,and the performance of BACS is tested by simulation experiments.The results show that,BACS accelerates the convergence speed of database query optimization and can obtain higher quality query optimization scheme.