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Optimum Operation of Reservoir Using Two Evolutionary Algorithms: Imperialist Competitive Algorithm (ICA) and Cuckoo Optimization Algorithm (COA)

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  • Seyed-Mohammad Hosseini-Moghari
  • Reza Morovati
  • Mohammad Moghadas
  • Shahab Araghinejad

Abstract

Water scarcity is one of the most serious problems in many parts of the world that affects negatively on the environment, society, and economy. In order to mitigate the negative effects of this issue, optimal water resource management is pivotal. In current paper, imperialist competitive algorithm (ICA) and cuckoo optimization algorithm (COA) which they are two new evolutionary methods, were used in optimal operation of reservoir. Firstly, these algorithms were used in solving several benchmark problems. Afterwards, optimal operation policy of Karun4 reservoir was extracted. Karun4 is located in Chaharmahal Va Bakhtiari province in western of Iran. Finally, the results which obtained from these methods were compared with genetic algorithm (GA) and nonlinear programing (NLP). In benchmark problems, COA converges to optimal point appropriately well and shows best performance. In these problems, ICA represent suitable ability to achieve global optimum. Both COA and ICA algorithms showed high performance in extraction of optimal operation policies from Karun4, which was conducted over a period of 360 months, with the aim of maximizing productivity. COA indicated the best performance with average value of 5.454 for objective function, and ICA with 6.461 value was at the second rank. In addition, GA objective function value was 6.869. Also NLP solver of Lingo11 was used in order to optimal operation of Karun4 reservoir for evaluating the ability of these algorithms to achieve global solution. Objective function value which was gained by NLP method was 5.243. The results reflect the strength of COA in approaching global optimum. Copyright Springer Science+Business Media Dordrecht 2015

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  • Seyed-Mohammad Hosseini-Moghari & Reza Morovati & Mohammad Moghadas & Shahab Araghinejad, 2015. "Optimum Operation of Reservoir Using Two Evolutionary Algorithms: Imperialist Competitive Algorithm (ICA) and Cuckoo Optimization Algorithm (COA)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3749-3769, August.
    • Handle: RePEc:spr:waterr:v:29:y:2015:i:10:p:3749-3769
    DOI: 10.1007/s11269-015-1027-6
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    4. Zhe Yang & Kan Yang & Hu Hu & Lyuwen Su, 2019. "The Cascade Reservoirs Multi-Objective Ecological Operation Optimization Considering Different Ecological Flow Demand," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(1), pages 207-228, January.
    5. Kobra Rahmati & Parisa-Sadat Ashofteh & Hugo A. Loáiciga, 2021. "Application of the Grasshopper Optimization Algorithm (GOA) to the Optimal Operation of Hydropower Reservoir Systems Under Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(13), pages 4325-4348, October.
    6. 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.
    7. Majid Mohammadi & Saeed Farzin & Sayed-Farhad Mousavi & Hojat Karami, 2019. "Investigation of a New Hybrid Optimization Algorithm Performance in the Optimal Operation of Multi-Reservoir Benchmark Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(14), pages 4767-4782, November.
    8. Zaher Mundher Yaseen & Mohammad Ehteram & Md. Shabbir Hossain & Chow Ming Fai & Suhana Binti Koting & Nuruol Syuhadaa Mohd & Wan Zurina Binti Jaafar & Haitham Abdulmohsin Afan & Lai Sai Hin & Nuratiah, 2019. "A Novel Hybrid Evolutionary Data-Intelligence Algorithm for Irrigation and Power Production Management: Application to Multi-Purpose Reservoir Systems," Sustainability, MDPI, vol. 11(7), pages 1-28, April.
    9. Iman Ahmadianfar & Bijay Halder & Salim Heddam & Leonardo Goliatt & Mou Leong Tan & Zulfaqar Sa’adi & Zainab Al-Khafaji & Raad Z. Homod & Tarik A. Rashid & Zaher Mundher Yaseen, 2023. "An Enhanced Multioperator Runge–Kutta Algorithm for Optimizing Complex Water Engineering Problems," Sustainability, MDPI, vol. 15(3), pages 1-28, January.
    10. Vijendra Kumar & S. M. Yadav, 2019. "Optimization of Cropping Patterns Using Elitist-Jaya and Elitist-TLBO Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(5), pages 1817-1833, March.
    11. Fatemeh Barzegari Banadkooki & Jan Adamowski & Vijay P. Singh & Mohammad Ehteram & Hojat Karami & Sayed Farhad Mousavi & Saeed Farzin & Ahmed EL-Shafie, 2020. "Crow Algorithm for Irrigation Management: A Case Study," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(3), pages 1021-1045, February.
    12. Bo Ming & Jian-xia Chang & Qiang Huang & Yi-min Wang & Sheng-zhi Huang, 2015. "Optimal Operation of Multi-Reservoir System Based-On Cuckoo Search Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5671-5687, December.

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