Hybrid greedy and genetic algorithms for optimization of relational data warehouses
Goran Velinov, Danilo Gligoroski, Margita Kon-Popovska · Conference on Artificial Intelligence for Applications · 2007
In this paper we present two novel algorithms for generalized problem of selection of optimal set of views, their optimal vertical fragmentation and their optimal set of indexes. The algorithms are hybrid, i.e. they are combination of Greedy and Genetic Algorithm. We present our experimental results and show that our algorithms significantly improve the efficiency of the optimization process for different input parameters. The results show that those algorithms outperforms Stochastic Ranking evolutionary (Genetic) Algorithm - SRGA by 60% - 280% in the speed of finding optimal (or near optimal) solutions.