Query optimization in distributed database using hybrid evolutionary algorithm

Join execution order, suitable copy selection from a query tables, join execution location selection and semijoin strategy are effective agents of a query´s execution plan´s cost. The selection of an optimal hybrid among these for agents for finding an execution plan is whit lowest cost of NP-Complete problems that in this paper is used from a hybrid evolutionary algorithm (EALA) for solving of this problem. This algorithm has used combination genetic algorithm and learning automata for producing optimal execution plan for a query. In this paper we compare the results from hybrid algorithm whit the results of genetic algorithm execution meaningful results are achieved.