To derive optimal operation policies from multi-reservoir systems, applying the conflict multiple goals simultaneously is very important. In order to, this paper presents a multi-objective optimization-simulation model, which is consist of agriculture and minimum flow goals in a three dam water resources system. For this purpose, a discrete hedging rule with a non-dominated sorting genetic algorithm has been coupled to minimize the modified shortage index over a series of hydrological record of 48 years. The evaluation metrics are diversity metric and standard deviation, which obtained values of each are equal to 0.357 and 0.0111 respectively. The results show the efficient performance of this algorithm to obtain Pareto frontier. Also, multi-objective algorithms present a set of optimum solutions for users instead of a solution, thus it helps to make decision in supplying the conflict goals of agriculture and minimum flow in different and complicate operation conditions such as drought periods easily.
Ahmadian far, I., Adib, A., Tghian, M., & haghighi, A. (2016). Optimization Operation from Storage Dams Using Non-Dominated Sorting Genetic Algorithm. Irrigation Sciences and Engineering, 39(2), 89-100. doi: 10.22055/jise.2016.12114
MLA
Iman Ahmadian far; Arash Adib; Mehrdad Tghian; Ali haghighi. "Optimization Operation from Storage Dams Using Non-Dominated Sorting Genetic Algorithm". Irrigation Sciences and Engineering, 39, 2, 2016, 89-100. doi: 10.22055/jise.2016.12114
HARVARD
Ahmadian far, I., Adib, A., Tghian, M., haghighi, A. (2016). 'Optimization Operation from Storage Dams Using Non-Dominated Sorting Genetic Algorithm', Irrigation Sciences and Engineering, 39(2), pp. 89-100. doi: 10.22055/jise.2016.12114
VANCOUVER
Ahmadian far, I., Adib, A., Tghian, M., haghighi, A. Optimization Operation from Storage Dams Using Non-Dominated Sorting Genetic Algorithm. Irrigation Sciences and Engineering, 2016; 39(2): 89-100. doi: 10.22055/jise.2016.12114
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