An Intelligentized Method of XML Query for Multiobjective Optimization Combined PSO and ACO

With the fast development of Web technology and its application, XML has become the important standard of information expression and data exchange on the Internet, XML functions have reached every corner of the network community. Considering the characteristics of XML for multi-objective optimization and the shortcomings of XML query, an optimization method using probabilistic rules of swarm intelligence algorithm is proposed. It adopts a path scattered rule, and combines PSO（particle swarm optimization） with ACO（ant colony optimization） to conduct dynamic swarm query by XML characteristics of semi-structured and the probabilistic rules to improve XML query, especially the PSO has the fast stochastic overall search ability, but it is unable to use the feedback information. The swarm actions are taken in turn towards the targets: swarm self-adaptive cross, encoding repeatedly, iterative choice, etc., which leads to the following good results: widening data search range, improving search precision and convergence efficiency, avoiding premature convergence, and reducing complexity of the algorithm. The simulation experiments show that the proposed combined method has a preferable query effectively.