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System performances analysis of reservoir optimization�simulation model in application of artificial bee colony algorithm

Decision making; Evolutionary algorithms; Genetic algorithms; Optimization; Particle swarm optimization (PSO); Reservoirs (water); Stochastic models; Stochastic systems; Artificial bee colonies (ABC); Artificial bee colony algorithms; Optimization techniques; Performance checking indices; Performanc...

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Main Authors: Hossain M.S., El-Shafie A., Mahzabin M.S., Zawawi M.H.
Other Authors: 55579596900
Format: Article
Published: Springer London 2023
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spelling my.uniten.dspace-236892023-05-29T14:51:02Z System performances analysis of reservoir optimization�simulation model in application of artificial bee colony algorithm Hossain M.S. El-Shafie A. Mahzabin M.S. Zawawi M.H. 55579596900 16068189400 56584655200 39162217600 Decision making; Evolutionary algorithms; Genetic algorithms; Optimization; Particle swarm optimization (PSO); Reservoirs (water); Stochastic models; Stochastic systems; Artificial bee colonies (ABC); Artificial bee colony algorithms; Optimization techniques; Performance checking indices; Performances analysis; Reservoir optimizations; Reservoir release; Stochastic dynamic programming; Dynamic programming In reservoir system operation, optimization is very much essential and the compatibility of different optimization techniques is essential to be checked by some performance checking indices. In this study, various types of performance-measuring index are used and compared to provide a complete knowledge on adopting different approaches. Here, the considered performance-measuring indicators will check the operation policy in terms of three different scenarios�how the method is efficient in achieving best results (reliability); how vulnerable the method is for different critical situation (vulnerability); and how capable it is to handle a failure of the model (resiliency). Therefore, the study proposed the artificial bee colony (ABC) optimization technique to develop an optimal water release policy for the well-known Aswan High Dam, Egypt. Particle swarm optimization, genetic algorithm and neural network-based stochastic dynamic programming are also used in a view of comparing model performances. A release curve is developed for every month as a guidance to the decision maker. Simulation has been done for each method using historical actual inflow data, and reliability, resiliency and vulnerability are measured. All model indicators proved that the release policy provided by ABC optimization outperforms in terms of achieving minimum water deficit, less waste of water and handling critical situations. � 2016, The Natural Computing Applications Forum. Final 2023-05-29T06:51:02Z 2023-05-29T06:51:02Z 2018 Article 10.1007/s00521-016-2798-2 2-s2.0-85007429410 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85007429410&doi=10.1007%2fs00521-016-2798-2&partnerID=40&md5=c356f233449198562e8b48f8dcdefecb https://irepository.uniten.edu.my/handle/123456789/23689 30 7 2101 2112 Springer London Scopus
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/
description Decision making; Evolutionary algorithms; Genetic algorithms; Optimization; Particle swarm optimization (PSO); Reservoirs (water); Stochastic models; Stochastic systems; Artificial bee colonies (ABC); Artificial bee colony algorithms; Optimization techniques; Performance checking indices; Performances analysis; Reservoir optimizations; Reservoir release; Stochastic dynamic programming; Dynamic programming
author2 55579596900
author_facet 55579596900
Hossain M.S.
El-Shafie A.
Mahzabin M.S.
Zawawi M.H.
format Article
author Hossain M.S.
El-Shafie A.
Mahzabin M.S.
Zawawi M.H.
spellingShingle Hossain M.S.
El-Shafie A.
Mahzabin M.S.
Zawawi M.H.
System performances analysis of reservoir optimization�simulation model in application of artificial bee colony algorithm
author_sort Hossain M.S.
title System performances analysis of reservoir optimization�simulation model in application of artificial bee colony algorithm
title_short System performances analysis of reservoir optimization�simulation model in application of artificial bee colony algorithm
title_full System performances analysis of reservoir optimization�simulation model in application of artificial bee colony algorithm
title_fullStr System performances analysis of reservoir optimization�simulation model in application of artificial bee colony algorithm
title_full_unstemmed System performances analysis of reservoir optimization�simulation model in application of artificial bee colony algorithm
title_sort system performances analysis of reservoir optimization�simulation model in application of artificial bee colony algorithm
publisher Springer London
publishDate 2023
_version_ 1806426538202103808
score 13.214268

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