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

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 opti...

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Main Authors: Yaseen, Z.M., Allawi, M.F., Karami, H., Ehteram, M., Farzin, S., Ahmed, A.N., Koting, S.B., Mohd, N.S., Jaafar, W.Z.B., Afan, H.A., El-Shafie, A.
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Language:English
Published: 2020
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spelling my.uniten.dspace-127662020-02-03T07:09:31Z A hybrid bat–swarm algorithm for optimizing dam and reservoir operation Yaseen, Z.M. Allawi, M.F. Karami, H. Ehteram, M. Farzin, S. Ahmed, A.N. Koting, S.B. Mohd, N.S. Jaafar, W.Z.B. Afan, H.A. El-Shafie, A. 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. © 2019, Springer-Verlag London Ltd., part of Springer Nature. 2020-02-03T03:26:37Z 2020-02-03T03:26:37Z 2019 Article 10.1007/s00521-018-3952-9 en
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language English
description 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. © 2019, Springer-Verlag London Ltd., part of Springer Nature.
format Article
author Yaseen, Z.M.
Allawi, M.F.
Karami, H.
Ehteram, M.
Farzin, S.
Ahmed, A.N.
Koting, S.B.
Mohd, N.S.
Jaafar, W.Z.B.
Afan, H.A.
El-Shafie, A.
spellingShingle Yaseen, Z.M.
Allawi, M.F.
Karami, H.
Ehteram, M.
Farzin, S.
Ahmed, A.N.
Koting, S.B.
Mohd, N.S.
Jaafar, W.Z.B.
Afan, H.A.
El-Shafie, A.
A hybrid bat–swarm algorithm for optimizing dam and reservoir operation
author_facet Yaseen, Z.M.
Allawi, M.F.
Karami, H.
Ehteram, M.
Farzin, S.
Ahmed, A.N.
Koting, S.B.
Mohd, N.S.
Jaafar, W.Z.B.
Afan, H.A.
El-Shafie, A.
author_sort Yaseen, Z.M.
title A hybrid bat–swarm algorithm for optimizing dam and reservoir operation
title_short A hybrid bat–swarm algorithm for optimizing dam and reservoir operation
title_full A hybrid bat–swarm algorithm for optimizing dam and reservoir operation
title_fullStr A hybrid bat–swarm algorithm for optimizing dam and reservoir operation
title_full_unstemmed A hybrid bat–swarm algorithm for optimizing dam and reservoir operation
title_sort hybrid bat–swarm algorithm for optimizing dam and reservoir operation
publishDate 2020
_version_ 1662758766790049792
score 13.222552

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