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Workshops on Applications of Evolutionary Computation

EvoWorkshops 2003: Applications of Evolutionary Computing pp 280–290Cite as

A Genetic Algorithm for the Index Selection Problem

Part of the Lecture Notes in Computer Science book series (LNCS,volume 2611)

Abstract

This paper considers the problem of minimizing the response time for a given database workload by a proper choice of indexes. This problem is NP-hard and known in the literature as the Index Selection Problem (ISP).

We propose a genetic algorithm (GA) for solving the ISP. Computational results of the GA on standard ISP instances are compared to branchand- cut method and its initialisation heuristics and two state of the art MIP solvers: CPLEX and OSL. These results indicate good performance, reliability and efficiency of the proposed approach.

Keywords

  • Genetic Algorithm
  • Answer Time
  • Uniform Crossover
  • Maintenance Time
  • Elitist Individual

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Author information

Authors and Affiliations

  1. Institute of Mathematics, Serbian Academy of Sciences and Arts, Kneza Mihajla 35/I, pp. 367, 11001, Belgrade, Yugoslavia

    Jozef Kratica

  2. Institute of Computer Graphics and Algorithms, Vienna University of Technology, Favoritenstraße 9-11/186, 1040, Vienna, Austria

    Ivana Ljubić

  3. Faculty of Mathematics, University of Belgrade, Studentski trg 16, Belgrade, Yugoslavia

    Dušan Tošić

Authors
  1. Jozef Kratica
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  2. Ivana Ljubić
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  3. Dušan Tošić
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Editor information

Editors and Affiliations

  1. Dept. of Computer Engineering, University of Parma, Parco Area delle Scienze 181/a, 43100, Parma, Italy

    Stefano Cagnoni

  2. Computing Laboratory, University of Kent, Canterbury, Kent, CT2 7NF, UK

    Colin G. Johnson

  3. Dept. of Information and Communications Technologies Faculty of Computer Science, University of A Coruña, A Coruña, CP 15071, Spain

    Juan J. Romero Cardalda

  4. Dept. of Mathematics and Computer Science, Free University of Amsterdam, de Boelelaan 1081a, 1081 HV, Amsterdam, The Netherlands

    Elena Marchiori

  5. Schol of Systems Engineering, University of Reading, PO Box 225, Whiteknights, Reading, RG6 6AY, UK

    David W. Corne

  6. AnimatLab, 8 rue du capitaine Scott, 75015, Paris, France

    Jean-Arcady Meyer & Agnès Guillot & 

  7. SAP AG, Neurottstrasse 16, 69190, Walldorf, Germany

    Jens Gottlieb

  8. Parallel Computing and Complex Systems Group, University of Leipzig, Augustusplatz 10/11, 04109, Leipzig, Germany

    Martin Middendorf

  9. Algorithms and Data Structures Group Institute of Computer Graphics, Vienna University of Technology, Favoritenstrasse 9-11/186, 1040, Vienna, Austria

    Günther R. Raidl

  10. School of Computing, Napier University, 219 Colinton Road, Edinburgh, EH14 1DJ, UK

    Emma Hart

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© 2003 Springer-Verlag Berlin Heidelberg

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Kratica, J., Ljubić, I., Tošić, D. (2003). A Genetic Algorithm for the Index Selection Problem. In: Cagnoni, S., et al. Applications of Evolutionary Computing. EvoWorkshops 2003. Lecture Notes in Computer Science, vol 2611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36605-9_26

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  • DOI: https://doi.org/10.1007/3-540-36605-9_26

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00976-4

  • Online ISBN: 978-3-540-36605-8

  • eBook Packages: Springer Book Archive

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