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Dynamic Programming Based Metaheuristic for Energy Planning Problems

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Applications of Evolutionary Computation (EvoApplications 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8602))

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Abstract

In this article, we propose DYNAMOP (DYNAmic programming using Metaheuristic for Optimization Problems) a new dynamic programming based on genetic algorithm to solve a hydro-scheduling problem. The representation which is based on a path in the graph of states of dynamic programming is adapted to dynamic structure of the problem and it allows to hybridize easily evolutionary algorithms with dynamic programming. DYNAMOP is tested on two case studies of hydro-scheduling problem with different price scenarios. Experiments indicate that the proposed approach performs considerably better than classical genetic algorithms and dynamic programming.

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Author information

Authors and Affiliations

  1. Inria Lille - Nord Europe, DOLPHIN Project-team, 59650, Villeneuve dAscq, France

    Sophie Jacquin, Laetitia Jourdan & El-Ghazali Talbi

  2. Université Lille 1, LIFL, UMR CNRS 8022, 59655, Villeneuve dAscq cedex, France

    Sophie Jacquin, Laetitia Jourdan & El-Ghazali Talbi

Authors
  1. Sophie Jacquin
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  2. Laetitia Jourdan
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  3. El-Ghazali Talbi
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Corresponding author

Correspondence to Sophie Jacquin .

Editor information

Editors and Affiliations

  1. Depto. Estadística e Investigación, Universidad Politécnica de Valencia, Valencia, Spain

    Anna I. Esparcia-Alcázar

  2. University of Granada, Granada, Spain

    Antonio M. Mora

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© 2014 Springer-Verlag Berlin Heidelberg

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Jacquin, S., Jourdan, L., Talbi, EG. (2014). Dynamic Programming Based Metaheuristic for Energy Planning Problems. In: Esparcia-Alcázar, A., Mora, A. (eds) Applications of Evolutionary Computation. EvoApplications 2014. Lecture Notes in Computer Science(), vol 8602. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45523-4_14

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  • DOI: https://doi.org/10.1007/978-3-662-45523-4_14

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-45522-7

  • Online ISBN: 978-3-662-45523-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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