利用启发式信息优化多连接查询的遗传算法

利用启发式信息优化多连接查询的遗传算法 A Genetic Algorithm Using Heuristics for Optimizing Large Join Queries 董红斌 DONG Hong bin 1 first-author 梁意文 LIANG Yi wen 1 康立山 KANG Li shan 1 陈毓屏 CHEN Yu ping 1 武汉大学软件工程国家重点实验室!计算机科学与技术学系武汉,430072 武汉大学软件工程国家重点实验室!计算机科学与技术学系武汉,430072 State Key Laboratory of Software Engineering/ Computer Science & Technology Department State Key Laboratory of Software Engineering/ Computer Science & Technology Department 结合多连接查询的特点，讨论了在左线性树空间的遗传优化算法，采用有序串编码方法和专门的杂交、变异算子；并利用查询优化中的增量启发式信息初始化种群，来提高遗传算法的收敛速度．我们将遗传算法与迭代修正的局部搜索策略相结合，解决传统的遗传算法缺乏较强的局部搜索功能的问题． The application of the GA to the optimization of the large JOIN queries in the space of the left deep strategies is considered. We present a ordering string as chromosomes , describe a special crossover operator and a mutation operator for such chromosomes, initiate population by augmentation heuristics,combine GA with local search technique to accelerate convergence. 遗传算法 查询优化 多连接查询 增量启发式 genetic algorithm query optimization large join queries augmentation heuristics TP311.13 国家863 计划资助 1999-05-01 2021-04-01 5