物化视图选择算法——ACSSA_VSP

Materialized view selection algorithm——ACSSA_VSP

本文对提高数据仓库查询效率的物化视图选择问题进行了研究。通过研究与实验,提出了一种改进的克隆选择算法解决物化视图选择问题,即在克隆选择算法变异过程中引入模拟退火算法的Metropolis准则,在保证抗体多样性的条件下提高了算法运行效率,同时在克隆选择算法选择过程中实现了每代更新数的自适应调节。由此提出了解决物化视图选择问题的自适应克隆选择模拟退火算法——ACSSA_VSP。理论分析和实验验证表明:ACSSA_VSP比解决物化视图选择问题常用的标准遗传算法求解质量更高、收敛速度更快。

In this paper,materialized view selection problem which can improve data warehouse query efficiency is studied.Through research and experiments,this paper proposes an improved clonal selection algorithm to solve materialized view selection problem,that is in the variation process of clonal selection algorithm the Metropolis criterion of simulated annealing algorithm is introduced which could improve algorithm running efficiency in the condition of ensuring antibody diversity,and at the same time in the selection process of clonal selection algorithm,the improved clonal selection algorithm realizes self adaptive adjustment of each generation renewal number.Thus this paper proposes adaptive clonal selection simulation annealing algorithm——ACSSA_VSP.Theoretical analysis and experimental verification show：ACSSA_VSP has better solution quality and quicker convergence speed than standard genetic algorithm often used to solve materialized view selection problem.