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. We apply one n Estimation of Distribution Algorithms (EDAs) to view selection under a size constraint. Our emphasis is to determine the suitability of the combination of EDAs with constraint handling to the view selection problem, compared to a widely used genetic algorithm. The EDAs are competitive with the genetic algorithm on a variety of problem instances, often finding approximate optimal solutions in a reasonable amount of time.
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