计算机工程2012，Vol.38Issue(1)：168-170,173,4.DOI:10.3969/j.issn.1000-3428.2012.01.053
基于改进蚁群算法的数据仓库多连接查询优化
Multi-join Query Optimization of Data Warehouse Based on Improved Ant Colony Algorithm
摘要
Abstract
Traditional Ant Colony Algorithm(ACA) is applied to solve the query optimization problem of Data Warehouse(DW), it has some shortcomings such as premature convergence and slowly convergence. This paper improves the traditional ACA to address these issues. The pseudo-random proportion rule is introduced to the Max-Min Ant System(MMAS), and the Iterated Local Search(ILS) strategy is performed after each iteration. Experimental results show that the improved algorithm accelerates the convergence rate of the algorithm and improves the quality of the optimal solution in solving multi-join query optimization.关键词
蚁群算法/迭代局部搜索/数据仓库/多连接查询优化/查询执行计划Key words
Ant Colony Algorithm(ACA)/ Iterated Local Search(ILS)/ Data Warehouse(DW)/ multi-join query optimization/ Query Execution Plan(QEP)分类
信息技术与安全科学引用本文复制引用
赵鹏,王守军,龚云..基于改进蚁群算法的数据仓库多连接查询优化[J].计算机工程,2012,38(1):168-170,173,4.基金项目
安徽省教育厅基金资助重点项目(KJ2009A001Z) （KJ2009A001Z）
安徽省科技厅重大科技专项基金资助项目(08010201002) （08010201002）
安徽大学青年科学研究基金资助项目(2009QN004A) （2009QN004A）
