Volume 22, Issue 1 (Spring 2018)                   jwss 2018, 22(1): 291-303 | Back to browse issues page

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Mohammadrezapour O, Zeynali M J. Comparison of Meta- Heuristic Algorithms in the Optimal Operation of Multi – Reservoir (A Case Study: Golestan and Voshmgir Dams). jwss 2018; 22 (1) :291-303
URL: http://jstnar.iut.ac.ir/article-1-3044-en.html
1. Dept. of Water Eng., Faculty of Water and Soil, Univ. of Zabol, Zabol, Iran. , nmohammadrezapour@yahoo.com
Abstract:   (7251 Views)
One of the most important issues in the field of optimizing water resources management is the optimal utilization of the dam reservoirs. In the recent decades, the optimal operation of dams has been one of the most interesting issues considered by water resources planners in the country. Due to the complexities of the typical optimization methods, employing an evolutionary algorithm is regarded here. One of the most significant algorithms is the ant colony algorithm. So the aim of this study is to optimize the delivery of Golestan and Voshmgir reservoirs to meet the needs of the down lands using the elite ant colony algorithm, maximum – minimum ants, ranked ants, and particle swarm algorithms, and to compare the performance of these algorithms with each other. The considered decision variable was the release of the reservoirs in the above- mentioned dams. In this study, the data over a 5-year period, from 2006-2007 to 2011-2012, was used for modeling. The results showed that all algorithms could optimize the release amount optimally; however, the elite ant algorithm with the objective function value of 0.6407 estimated the release values with great accuracy in both dams. Also, the particle swarm algorithm with 1.275 of the objective function value was well-matched with the release values.  The ranked ant algorithm with 18.924 and Max-Min ant with 26.431 of the objective function valuewere, respectively, at the next levels of performance optimization of the release values from Golestan and Voshgar dams.
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Type of Study: Research | Subject: Ggeneral
Received: 2015/08/5 | Accepted: 2018/02/24 | Published: 2018/06/15

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