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Application of Intelligent Water Drops Algorithm in Reservoir Operation

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  • A. Dariane
  • S. Sarani

Abstract

Optimum reservoir operation is a challenging problem in water resources systems. In this paper, Intelligent Water Drops (IWD) algorithm is applied in a reservoir operation problem. IWD is a population based algorithm and is initially proposed for solving combinatorial problems. The algorithm mimics the dynamics of river system and the behavior of water drops in the rivers. For this purpose data from Dez reservoir, located in southwestern Iran, has been used to examine the performance of the model. Moreover, due to similarities between IWD and the Ant Colony Optimization (ACO) algorithms, the results are compared with those of the ACO algorithm. Comparison of the results shows that while the IWD algorithm finds relatively better solutions, it is able to overcome the computational time consumption deficiencies inherited in the ACO methods. This is very important in large models with too many decision variables where run time becomes a limiting factor for optimization model applications. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • A. Dariane & S. Sarani, 2013. "Application of Intelligent Water Drops Algorithm in Reservoir Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(14), pages 4827-4843, November.
    • Handle: RePEc:spr:waterr:v:27:y:2013:i:14:p:4827-4843
    DOI: 10.1007/s11269-013-0441-x
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    References listed on IDEAS

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    1. Omid Haddad & Abbas Afshar & Miguel Mariño, 2006. "Honey-Bees Mating Optimization (HBMO) Algorithm: A New Heuristic Approach for Water Resources Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(5), pages 661-680, October.
    2. Rama Mehta & Sharad Jain, 2009. "Optimal Operation of a Multi-Purpose Reservoir Using Neuro-Fuzzy Technique," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(3), pages 509-529, February.
    3. M. Shourian & S. Mousavi & A. Tahershamsi, 2008. "Basin-wide Water Resources Planning by Integrating PSO Algorithm and MODSIM," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(10), pages 1347-1366, October.
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    Cited by:

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    2. Asmadi Ahmad & Siti Fatin Mohd Razali & Zawawi Samba Mohamed & Ahmed El-shafie, 2016. "The Application of Artificial Bee Colony and Gravitational Search Algorithm in Reservoir Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(7), pages 2497-2516, May.
    3. Asmadi Ahmad & Ahmed El-Shafie & Siti Razali & Zawawi Mohamad, 2014. "Reservoir Optimization in Water Resources: a Review," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(11), pages 3391-3405, September.
    4. Fang Wan & Wenlin Yuan & Jin Zhou, 2017. "Derivation of Tri-level Programming Model for Multi-Reservoir Optimal Operation in Inter-Basin Transfer-Diversion-Supply Project," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(1), pages 479-494, January.

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