JWSS - Journal of Water and Soil Science

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.

Exploitation of dam reservoirs is one of the major problems in the management of water resources. In this research, Crow Search Algorithm (CSA) was used for the first time to manage the operation of reservoirs. Also, the results related to the exploitation of the single-reservoir system of Shahid-Rajaei dam, located in Mazandaran province, northern Iran, which meets the downstream water demands, were compared to those obtained by applying the Particle Swarm and Genetic algorithms. Time reliability, volume reliability, vulnerability and reversibility indices, and a multi-criteria decision-making model were used to select the best algorithm. The results showed that the CSA obtained results close to the problem’s absolute optimal response, such that the average responses in the Crow, Particle Swarm and Genetic Algorithms were 99, 75 and 61 percent of the absolute optimal response, respectively. Besides, except for the time reliability index, the CSA had a better performance in the rest of the indices, as compared to Particle Swarm and Genetic Algorithms. The coefficient of variation of the obtained responses by CSA was 14 and 16 times smaller than the Genetic and Particle Swarm Algorithms, respectively. The multi-criteria decision-making model revealed that the CSA was ranked first, as compared to the other two algorithms, in the Shahid-Rajaei Reservoir's operation problem.