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Optimizing web page layout using an annealed genetic algorithm as client-side script

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Parallel Problem Solving from Nature — PPSN V (PPSN 1998)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1498))

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Abstract

The high volume of information available on the Internet makes it necessary to use search and organization tools to filter and display it. This presentation must make efficient use of the surface the browser leaves; this is even more true in the case of personalized newspapers, in which all the news and publicity must be presented in only one “coup d'oeil”, to make them as effective as possible. In this paper, a system to automatically paginate web newspapers on the browser is presented. The system uses a genetic algorithm with integer representation and variable mutation amplitude, fine-tuned by a greedy algorithm. This combination proves to be much better than the genetic algorithm alone. The algorithm is proved to be able to lay out the web page in real time, that is, a time insignificant with respect to the time it takes to load an average page. The system will be embedded in several personalized news sites that are being developed at Granada University.

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Authors and Affiliations

  1. Department of Architecture and Computer Technology, University of Granada, Spain

    J. González Peñalver & J. J. Merelo

Authors
  1. J. González Peñalver
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  2. J. J. Merelo
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Editor information

Agoston E. Eiben Thomas Bäck Marc Schoenauer Hans-Paul Schwefel

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© 1998 Springer-Verlag Berlin Heidelberg

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Peñalver, J.G., Merelo, J.J. (1998). Optimizing web page layout using an annealed genetic algorithm as client-side script. In: Eiben, A.E., Bäck, T., Schoenauer, M., Schwefel, HP. (eds) Parallel Problem Solving from Nature — PPSN V. PPSN 1998. Lecture Notes in Computer Science, vol 1498. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0056943

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  • DOI: https://doi.org/10.1007/BFb0056943

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65078-2

  • Online ISBN: 978-3-540-49672-4

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