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Multi-Objective Firefly Integration with the K-Nearest Neighbor to Reduce Simulation Model Calls to Accelerate the Optimal Operation of Multi-Objective Reservoirs

Author

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  • Mahboubeh Khorsandi

    (University of Qom)

  • Parisa-Sadat Ashofteh

    (University of Qom)

  • Firoozeh Azadi

    (University of Qom)

  • Xuefeng Chu

    (North Dakota State University)

Abstract

Reservoirs are used as one of the surface water sources for different and often conflicting water supply purposes. Given the complex management policies governing a basin, it is essential to simultaneously consider different goals and cope with the associated trade-off in water resources management. This purpose requires coupling a multi-objective optimization algorithm with a reservoir simulation model, which this approach increases required computational efforts. Various simulation–optimization approaches have been developed and used for solving the related problems. However, they often have complicated methods and certain limitations in real-world applications. In this study, a new multi-objective firefly algorithm—K nearest neighbor (MOFA-KNN) hybrid algorithm is developed which is time-efficient and is not as complicated as previous approaches. The proposed algorithm was evaluated for both benchmark and real problems. The results of the benchmark problem showed that the execution time of the MOFA-KNN hybrid algorithm was up to 99.98% less than that of the multi-objective firefly algorithm (MOFA). In the real problem, the MOFA-KNN algorithm was linked to the 2D hydrodynamic and water quality model, CE-QUAL-W2, to test the developed framework for reservoir operation. The Aidoghmoush reservoir as a case study investigated to minimize the total released dissolved solids (TDS) and the water temperature difference between the inflow and the outflow. The results demonstrated that the MOFA-KNN algorithm significantly reduced the simulation–optimization execution time (> 660 times compared with MOFA). The minimum released TDS from the reservoir was 13.6 mg /l and the minimum temperature difference was 0.005 °C.

Suggested Citation

  • Mahboubeh Khorsandi & Parisa-Sadat Ashofteh & Firoozeh Azadi & Xuefeng Chu, 2022. "Multi-Objective Firefly Integration with the K-Nearest Neighbor to Reduce Simulation Model Calls to Accelerate the Optimal Operation of Multi-Objective Reservoirs," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(9), pages 3283-3304, July.
    • Handle: RePEc:spr:waterr:v:36:y:2022:i:9:d:10.1007_s11269-022-03201-5
    DOI: 10.1007/s11269-022-03201-5
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    References listed on IDEAS

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    1. Navid Shenava & Mojtaba Shourian, 2018. "Optimal Reservoir Operation with Water Supply Enhancement and Flood Mitigation Objectives Using an Optimization-Simulation Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(13), pages 4393-4407, October.
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    Cited by:

    1. Mahta Nazari & Reza Kerachian, 2024. "Optimal Operation of Reservoirs Considering Water Quantity and Quality Aspects: A Systematic State-of-the-Art Review," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(15), pages 5911-5944, December.
    2. Behrang Beiranvand & Parisa-Sadat Ashofteh, 2023. "A Systematic Review of Optimization of Dams Reservoir Operation Using the Meta-heuristic Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(9), pages 3457-3526, July.

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