A data warehouse contains multiple views accessed by queries. One of the most important decisions in designing a data warehouse is the selection of materialized views for the purpose of efficiently implementing decision making. The search space for the selection of materialized views is exponentially large, therefore, heuristics have been used to search a small fraction of the space to get a near optimal solution. In this paper, we explore the use of a genetic algorithm for the selection of materialized views based on multiple global processing plans for many queries. Our experimental studies indicate that the genetic algorithm delivers better solutions than some heuristics. © 1999 IEEE.