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Optimization of Water Resources Utilization by Multi-Objective Moth-Flame Algorithm

Author

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  • Wei Kun Li

    (Zhejiang University of Technology)

  • Wan Liang Wang

    (Zhejiang University of Technology)

  • Li Li

    (Guilin University of Electronic Technology)

Abstract

With the increasing power demand and rapid depletion of conventional fossil fuel resources, hydroelectric power resource has caused great attention of the public. A multi reservoir system with multiple objectives including ecological water demand, hydropower generation, and water diversion in Lushui River basin in China is under consideration in this context. Aiming to improve the efficiency of the water resources utilization, a novel method called multi-objective Moth-flame optimization algorithm (MOMFA) has been applied into this problem. The proposed algorithm involves the effective properties of the original Moth-flame optimization algorithm and two efficient mechanisms named opposition-based learning and indicator-based selection have also been integrated into the algorithm with the purpose of assisting the algorithm to accelerate the convergence and maintain the diversity simultaneously. The performance of the proposed MOMFA tested on a series of benchmarks and the Lushui River Basin. The result indicated that the proposed algorithm is not only capable of obtaining the well pareto solutions on standard problem but also can find the best tradeoff of the components and simultaneously achieve a set of well distributed non-dominated solutions for the multi-objective water resources utilization problem. Compare with the results obtained by other algorithms, the superiority of the proposed MOMFA has also been verified.

Suggested Citation

  • Wei Kun Li & Wan Liang Wang & Li Li, 2018. "Optimization of Water Resources Utilization by Multi-Objective Moth-Flame Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(10), pages 3303-3316, August.
    • Handle: RePEc:spr:waterr:v:32:y:2018:i:10:d:10.1007_s11269-018-1992-7
    DOI: 10.1007/s11269-018-1992-7
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    References listed on IDEAS

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    1. Aida Tayebiyan & Thamer Ahmed Mohammed Ali & Abdul Halim Ghazali & M. A. Malek, 2016. "Optimization of Exclusive Release Policies for Hydropower Reservoir Operation by Using Genetic Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(3), pages 1203-1216, February.
    2. 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.
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    Cited by:

    1. Djaafar Zouache & Fouad Ben Abdelaziz & Mira Lefkir & Nour El-Houda Chalabi, 2021. "Guided Moth–Flame optimiser for multi-objective optimization problems," Annals of Operations Research, Springer, vol. 296(1), pages 877-899, January.
    2. Ting Wang & Yu Liu & Ying Wang & Xinmin Xie & Jinjun You, 2019. "A Multi-Objective and Equilibrium Scheduling Model Based on Water Resources Macro Allocation Scheme," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(10), pages 3355-3375, August.

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