高斯扰动粒子群算法的数据库查询优化

Query Optimization of Database Based on Gauss Mutation Quantum Behaved Particle Swarm of Optimization Algorithm

针对量子粒子群算法存在的不足,将变异算子引入其中,提出一种高斯变异量子粒子群算法(GM-QPSO),并将其应用于数据库查询优化中.首先建立数据库查询优化数学模型,然后采用量子粒子代表一个可行的数据库查询方案,然后通过量子粒子之间的信息交流,找到数据库查询最优解,最后在Matlab 2012上进行了仿真实验.仿真结果表明,GM-QPSO克服了量子粒子群算法存在的不足,不仅提高了数据库查询速度,而且获得了更加理想的查询优化方案.

In order to solve the defect of quantum particle swarm algorithm, mutation operator of the genetic algorithm is introduced into quantum particle swarm optimization algorithm. It produces a novel query optimization method of database（GM-QPSO）. Firstly, the mathematic model is established for database query optimization problems. And then the optimal scheme of database query optimization problems is found by the sharing message of quantum particle. Finally, the simulation experiments is carried out on Matlab 2012. The results show that the proposed algorithm has solved the defect of quantum particle swarm algorithm, and improved query speed of database and can obtain better query scheme.