Genetic algorithm for the multiple-query optimization problem

Date

2007-01-01

Author

Bayir, Murat Ali
Toroslu, İsmail Hakkı
Coşar, Ahmet

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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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.

Subject Keywords

Database Query Processing, Genetic Algorithms (GA), Heuristics Techniques, Multiple-Query Optimization (MQO)

URI

https://hdl.handle.net/11511/32476

Journal

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS

DOI

https://doi.org/10.1109/tsmcc.2006.876060

Collections

Graduate School of Natural and Applied Sciences, Article

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Citation Formats

M. A. Bayir, İ. H. Toroslu, and A. Coşar, “Genetic algorithm for the multiple-query optimization problem,” IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS, pp. 147–153, 2007, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/32476.