| 摘要: |
| 针对单一普通算法在查询优化方面的不足，提出了一种结合遗传算法与蚁群算法优点的多蚁群遗传算法，克服了蚁群算法前期搜索的盲目性，并引入多蚁群概念，更好地防止了算法陷入局部最优的情况，以获取更优的查询路径.类比实验表明，该算法较传统蚁群算法，在查询方面，能获得更好的查询路径. |
| 关键词: 分布式数据库 多蚁群 遗传算法 查询优化 |
| DOI：10.3969/J.ISSN.1000-5137.2018.01.006 |
| 分类号: |
| 基金项目: |
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| Query optimization of distributed database based on multiple ant colony genetic algorithm |
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Zhou Ying, Chen Junhua
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The College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China
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| Abstract: |
| In the light of the defect of single algorithm of query optimization,this paper proposes a multiple ant colony genetic algorithm combining the advantages of ant colony algorithm and genetic algorithmwhich overcomes the blindness of early search of ant colony algorithm.Moreover the introduction of multi ant colony concept better prevents the algorithm falling into local optimal conditions as to obtain better query path..The final experiment results show that the improved optimization algorithm can find better query path in the query compared with the traditional ant colony algorithm. |
| Key words: distributed database multi ant-colony genetic algorithm query optimization |
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