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A hybrid bat–swarm algorithm for optimizing dam and reservoir operation

  • Zaher Mundher Yaseen
  • Mohammed Falah Allawi
  • Hojat Karami
  • Mohammad Ehteram
  • Saeed Farzin
  • Ali Najah Ahmed
  • Suhana Binti Koting
  • Nuruol Syuhadaa Mohd
  • Wan Zurina Binti Jaafar
  • Haitham Abdulmohsin Afan
  • Ahmed El-Shafie
Original Article
  • 32 Downloads

Abstract

One of the major challenges and difficulties to generate optimal operation rule for dam and reservoir operation are how efficient the optimization algorithm to search for the global optimal solution and the time-consume for convergence. Recently, evolutionary algorithms (EA) are used to develop optimal operation rules for dam and reservoir water systems. However, within the EA, there is a need to assume internal parameters at the initial stage of the model development, such assumption might increase the ambiguity of the model outputs. This study proposes a new hybrid optimization algorithm based on a bat algorithm (BA) and particle swarm optimization algorithm (PSOA) called the hybrid bat–swarm algorithm (HB-SA). The main idea behind this hybridization is to improve the BA by using the PSOA in parallel to replace the suboptimal solution generated by the BA. The solutions effectively speed up the convergence procedure and avoid the trapping in local optima caused by using the BA. The proposed HB-SA is validated by minimizing irrigation deficits using a multireservoir system consisting of the Golestan and Voshmgir dams in Iran. In addition, different optimization algorithms from previous studies are investigated to compare the performance of the proposed algorithm with existing algorithms for the same case study. The results showed that the proposed HB-SA algorithm can achieve minimum irrigation deficits during the examined period and outperforms the other optimization algorithms. In addition, the computational time for the convergence procedure is reduced using the HB-SA. The proposed HB-SA is successfully examined and can be generalized for several dams and reservoir systems around the world.

Keywords

Particle swarm optimization Multireservoir system Bat algorithm Optimization model 

Notes

Acknowledgements

This research was funded by a University of Malaya Research Grant “UMRG” (RP025A-18SUS). The authors are grateful to the University of Malaya, Malaysia, for supporting this study. The authors also would like to acknowledge the Universiti Tenaga Nasional for the financial support under Bold Grant 10289176/B/9/2017/14.

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  • Zaher Mundher Yaseen
    • 1
  • Mohammed Falah Allawi
    • 2
  • Hojat Karami
    • 3
  • Mohammad Ehteram
    • 3
  • Saeed Farzin
    • 3
  • Ali Najah Ahmed
    • 4
    • 5
  • Suhana Binti Koting
    • 6
  • Nuruol Syuhadaa Mohd
    • 6
  • Wan Zurina Binti Jaafar
    • 6
  • Haitham Abdulmohsin Afan
    • 6
  • Ahmed El-Shafie
    • 6
  1. 1.Sustainable Developments in Civil Engineering Research Group, Faculty of Civil EngineeringTon Duc Thang UniversityHo Chi Minh CityVietnam
  2. 2.Civil and Structural Engineering Department, Faculty of Engineering and Built EnvironmentUniversiti Kebangsaan MalaysiaBandar Baru BangiMalaysia
  3. 3.Department of Water Engineering and Hydraulic Structures, Faculty of Civil EngineeringSemnan UniversitySemnanIran
  4. 4.College of EngineeringUniversiti Tenaga NasionalKajangMalaysia
  5. 5.Institute of Energy InfrastructuresUniversiti Tenaga NasionalKajangMalaysia
  6. 6.Civil Engineering Department, Faculty of EngineeringUniversity of MalayaKuala LumpurMalaysia

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