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An evolutionary algorithm for resource-constrained project scheduling and multiple execution modes

  • Genetic Algorithms
  • Conference paper
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Advances in Artificial Intelligence (SBIA 1996)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1159))

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Abstract

This paper is concerned with the problem of resource-constrained project scheduling under multiple performing modes. A heuristic solution based on Genetic Algorithms is proposed. Furthermore, the resource leveling concept is incorporated into the procedure as a form of guidance in the search of a solution that yields not only the shortest duration, but a leveled solution as well. A comparison with more traditional approaches is provided using benchmarks available in the literature. The results show the efficiency of the proposed algorithm.

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Authors and Affiliations

  1. Programa de Pós-Graduação em Engenharia de Produção, Universidade Federal de Santa Catarina, Cx.P. 476, CEP 88040-900, Florianópolis, SC

    Oscar Ciro López Dr., Ricardo M. Barcia Ph.D & Fernando O. Gauthier Dr.

  2. Department of Industrial and System Engineering, Virginia Polytechnic Institute and State University, 24061-0118, Blacksburg, Virginia, USA

    Osama Eyada Ph.D

Authors
  1. Oscar Ciro López Dr.
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  2. Ricardo M. Barcia Ph.D
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  3. Osama Eyada Ph.D
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  4. Fernando O. Gauthier Dr.
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Editor information

Díbio L. Borges Celso A. A. Kaestner

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© 1996 Springer-Verlag Berlin Heidelberg

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López, O.C., Barcia, R.M., Eyada, O., Gauthier, F.O. (1996). An evolutionary algorithm for resource-constrained project scheduling and multiple execution modes. In: Borges, D.L., Kaestner, C.A.A. (eds) Advances in Artificial Intelligence. SBIA 1996. Lecture Notes in Computer Science, vol 1159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61859-7_11

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  • DOI: https://doi.org/10.1007/3-540-61859-7_11

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61859-1

  • Online ISBN: 978-3-540-70742-4

  • eBook Packages: Springer Book Archive

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