Abstract: The data cube selection problem is known to be an NP-hard problem. In this study, we examined the applicalion of genetic algorithms to the cube selection problem. We proposed a genetic local search algorithm. The core idea of the algorithm is as follows. First, a pre-process algorithm based on the maximum benefit per unit space was used to generate initial solutions. Then, the initial solutions were improved by genetic algorithm having the local search of optimal strategies. The experimental results show that the proposed algorithm outperforms heuristic algorithm and canonical genctic algorithm.

Key words: Query optimization, Uenetic algorithms, Data warehousing, OLAP, View selection