Study of Multi Ant Colony Genetic Algorithm in Query Optimization of Distributed Database

Under the background of "Internet plus" era, the amount of information in every field is increasing geometrically. Human beings are faced with massive data analysis and process every day. In this context, the application scenario of distributed database is gradually increasing. The speed of query operation is the key index that affects the efficiency of distributed database. A reasonable and efficient algorithm is of great practical significance to improve the query efficiency of database and to speed up the query process. In the past, a single conventional algorithm which was used to optimize query operations exposed some defects were exposed when a single conventional algorithm was used to optimize query operations, such as no planning, local advance into the optimal state local entry into optimal state in advance, long time of query and so on. In view of this, combined with the advantages of genetic algorithm and ant colony algorithm, this paper proposes a multi-ant colony genetic algorithm of query optimization of distributed database. Simulation results show that compared with traditional ant colony algorithm, the improved algorithm significantly enhances the execution ability and query efficiency of distributed database. In the aspect of optimization of distributed database, it has great value of promotion.