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Innovations and Advances in Computer Sciences and Engineering pp 407–411Cite as

A new approach for critical resources allocation

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Abstract

This paper presents a solution based on Artificial Intelligence using Multi-objective Genetic Algorithms to optimize the allocation of teachers and classrooms. The implementation was created in order to optimize the process in both cases, allowing them to compete so as to establish a balance and arrive at a feasible solution quickly and efficiently.

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V References

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Author information

Authors and Affiliations

  1. ITLab, Universidad de Palermo, Ciudad Autónoma de Buenos Aires, Palermo, C1188AAB, Argentina

    Facundo E. Cancelo, Pablo Cababie, Daniela López De Luise & Gabriel Barrera

Authors
  1. Facundo E. Cancelo
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  2. Pablo Cababie
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  3. Daniela López De Luise
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  4. Gabriel Barrera
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Corresponding author

Correspondence to Facundo E. Cancelo .

Editor information

Editors and Affiliations

  1. School of Engineering, University of Bridgeport, University Avenue 221, Bridgeport, 06604, U.S.A.

    Tarek Sobh

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© 2010 Springer Science+Business Media B.V.

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Cite this paper

Cancelo, F.E., Cababie, P., De Luise, D.L., Barrera, G. (2010). A new approach for critical resources allocation. In: Sobh, T. (eds) Innovations and Advances in Computer Sciences and Engineering. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3658-2_71

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  • DOI: https://doi.org/10.1007/978-90-481-3658-2_71

  • Published:

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-3657-5

  • Online ISBN: 978-90-481-3658-2

  • eBook Packages: EngineeringEngineering (R0)

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