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Genetic Algorithm for the Multiple-Query Optimization Problem
Murat Ali Bayir   Ismail H. Toroslu   Ahmet Cosar  
Comput. Eng. Dept., Middle East Tech. Univ., Ankara;

This paper appears in: Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
Publication Date: Jan. 2007
Volume: 37,  Issue: 1
On page(s): 147-153
ISSN: 1094-6977
INSPEC Accession Number: 9368978
Digital Object Identifier: 10.1109/TSMCC.2006.876060
Current Version Published: 2006-12-19

Abstract
Producing answers to a set of queries with common tasks efficiently is known as the multiple-query optimization (MQO) problem. Each query can have several alternative evaluation plans, each with a different set of tasks. Therefore, the goal of MQO is to choose the right set of plans for queries which minimizes the total execution time by performing common tasks only once. Since MQO is an NP-hard problem, several, mostly heuristics based, solutions have been proposed for solving it. To the best of our knowledge, this correspondence is the first attempt to solve MQO using an evolutionary technique, genetic algorithms

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