Paper Title:
The HGEDA Hybrid Algorithm for OLAP Data Cubes
  Abstract

On-Line Analytical Processing (OLAP) tools are frequently used in business, science and health to extract useful knowledge from massive databases. An important and hard optimization problem in OLAP data warehouses is the view selection problem, consisting of selecting a set of aggregate views of the data for speeding up future query processing. In this paper we present a new approach, named HGEDA, which is a new hybrid algorithm based on genetic and estimation of distribution algorithms. The original objective is to get benefits from both approaches. Experimental results show that the HGEDA are competitive with the genetic algorithm on a variety of problem instances, often finding approximate optimal solutions in a reasonable amount of time.

  Info
Periodical
Edited by
Han Zhao
Pages
3158-3162
DOI
10.4028/www.scientific.net/AMM.130-134.3158
Citation
C. Jia, H. W. Chen, "The HGEDA Hybrid Algorithm for OLAP Data Cubes", Applied Mechanics and Materials, Vols. 130-134, pp. 3158-3162, 2012
Online since
October 2011
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