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Bi-Attempted Base Optimization Algorithm on Optimization of Hydrosystems

Author

Listed:
  • Burhan Yildiz

    (Mugla Sitki Kocman University
    Delft University of Technology)

  • Mehtap Kose Ulukok

    (Cyprus Science University)

  • Vali Bashiry

    (Cyprus International University)

Abstract

This study aims to search for optimum design parameters for a slurry pipeline problem and optimum operation parameters for a multi-reservoir scheduling problem by using Bi-Attempted Base Optimization Algorithm (ABaOA), which has been recently developed as a numerical bidirectional search algorithm. The slurry pipeline problem is a constrained non-linear cost minimization problem with constraints on facility capacities. It has two separate cost terms that behave differently with changes in decision variables. The problem includes several decision variables in addition to the fact that the objective function is highly non-linear. On the other hand, the multi-reservoir problem is a well-known problem in Hydraulics that aims to maximize benefit by optimizing the releases of each reservoir. The problem has a known global optimum, which is used to test the abilities of the ABaOA. The ABaOA is developed from Base Optimization Algorithm (BaOA) by transforming its operators with the aim to diversify the search paths to reach the global optimum. Its applications in hydrosystems show that it converges to the optimum solutions in reasonable times. The results from the first application are compared to the ones obtained from Genetic Algorithms (GA) application. It is observed that ABaOA outperformed GA in terms of speed of convergence and finding a better alternative solution. The ABaOA reaches the global optimum in the second application. In addition, alternatives with better benefit functions, including some penalties have been determined.

Suggested Citation

  • Burhan Yildiz & Mehtap Kose Ulukok & Vali Bashiry, 2023. "Bi-Attempted Base Optimization Algorithm on Optimization of Hydrosystems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(9), pages 3585-3597, July.
    • Handle: RePEc:spr:waterr:v:37:y:2023:i:9:d:10.1007_s11269-023-03517-w
    DOI: 10.1007/s11269-023-03517-w
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    References listed on IDEAS

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    1. Youngje Choi & Jungwon Ji & Eunkyung Lee & Sunmi Lee & Sooyeon Yi & Jaeeung Yi, 2023. "Developing Optimal Reservoir Rule Curve for Hydropower Reservoir with an add-on Water Supply Function Using Improved Grey Wolf Optimizer," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(5), pages 2063-2082, March.
    2. Onur Hınçal & A. Altan-Sakarya & A. Metin Ger, 2011. "Optimization of Multireservoir Systems by Genetic Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(5), pages 1465-1487, March.
    3. Xiang Zhang & Liangkun Deng & Bi Wu & Shichun Gao & Yi Xiao, 2022. "Low-Impact Optimal Operation of a Cascade Sluice-Reservoir System for Water-Society-Ecology Trade-Offs," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(15), pages 6131-6148, December.
    4. Yuxin Zhu & Jianzhong Zhou & Yongchuan Zhang & Zhiqiang Jiang & Benjun Jia & Wei Fang, 2022. "Optimal Energy Storage Operation Chart and Output Distribution of Cascade Reservoirs Based on Operating Rules Derivation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(14), pages 5751-5766, November.
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