Genetic Algorithm for the Multiple-Query Optimization Problem

Author

Bayir, Murat Ali ; Toroslu, Ismail H. ; Cosar, Ahmet

Author_Institution

Comput. Eng. Dept., Middle East Tech. Univ., Ankara

Volume

37

Issue

1

fYear

2007

Firstpage

147

Lastpage

153

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

Keywords

computational complexity; database management systems; genetic algorithms; query processing; NP-hard problem; genetic algorithm; multiple-query optimization problem; Algebra; Costs; Genetic algorithms; NP-hard problem; Optimization methods; Query processing; Relational databases; Database query processing; genetic algorithms (GA); heuristics techniques; multiple-query optimization (MQO);

fLanguage

English

Journal_Title

Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on

Publisher

ieee

ISSN

1094-6977

Type

jour

DOI

10.1109/TSMCC.2006.876060

Filename

4032932