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Evolutionary Algorithms and Water Resources Optimization

  • Conference paper
EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 175))

Abstract

Heuristic optimization models with varying degree of complexity have been widely applied for resolving water resources optimization and allocation problems. Nevertheless, there still exist uncertainties about finding a generally consistent and trustworthy method that can find solutions, which are really close to the global optimum in all circumstances. This paper makes a review of some of the numerous evolutionary optimization algorithms available to water resources planners and managers. Evolutionary algorithms have been found propitious and useful in facilitating critical water management decisions and are becoming promising global optimization tools for major real world applications. Further research aimed at developing optimization models for water resources planning, management and optimization is therefore necessary.

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Authors and Affiliations

  1. Durban University of Technology, Durban, South Africa

    Oluwatosin Olofintoye, Josiah Adeyemo & Fred Otieno

Authors
  1. Oluwatosin Olofintoye
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  2. Josiah Adeyemo
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  3. Fred Otieno
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Corresponding author

Correspondence to Oluwatosin Olofintoye .

Editor information

Editors and Affiliations

  1. , Computer Science Department, CINVESTAV-IPN, Col. San Pedro Zacatenco 2508, Mexico City, 07360, Mexico

    Oliver Schütze

  2. , Computer Science Department, CINVESTAV-IPN, Col. San Pedro Zacatenco 2508, Mexico City, 07360, Mexico

    Carlos A. Coello Coello

  3. , Computer Science and Communications, University of Luxembourg, rue Richard Coudenhove-Kalergi 6, Luxembourg, 1359, Luxembourg

    Alexandru-Adrian Tantar

  4. Computer Science and Communications, Research Unit, University of Luxembourg, rue Richard Coudenhove-Kalergi 6, Luxembourg, L-1359, Luxembourg

    Emilia Tantar

  5. Computer Science, and Communications, University of Luxembourg, rue Richard Coudenhove-Kalergi 6, Luxembourg, L-1359, Luxembourg

    Pascal Bouvry

  6. Bordeaux Mathematical Institute, INRIA Bordeaux-Sud Ouest, Université Bordeaux I, cours de la Libération 351, Talence Cedex, 33405, France

    Pierre Del Moral

  7. Bâtiment Leyteire, UFR Sciences et Modélisation, Université Bordeaux II, 3ter place de la Victoire, Bordeaux, 33000, France

    Pierrick Legrand

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Olofintoye, O., Adeyemo, J., Otieno, F. (2013). Evolutionary Algorithms and Water Resources Optimization. In: Schütze, O., et al. EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II. Advances in Intelligent Systems and Computing, vol 175. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31519-0_32

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  • DOI: https://doi.org/10.1007/978-3-642-31519-0_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31518-3

  • Online ISBN: 978-3-642-31519-0

  • eBook Packages: EngineeringEngineering (R0)

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