MULTI-OBJECTIVE OPTIMIZATION OF THE HEDGING MODEL FOR RESERVOIR OPERATION USING EVOLUTIONARY ALGORITHMS

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SADEGHI TABAS S.; POURREZA BILANDI M.; TAGHIAN M.

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Journal: WATER AND WASTEWATER Year:2015 | Volume:26 | Issue:5 (99) Page(s): 14-22

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Title

MULTI-OBJECTIVE OPTIMIZATION OF THE HEDGING MODEL FOR RESERVOIR OPERATION USING EVOLUTIONARY ALGORITHMS

Author(s)

SADEGHI TABAS S. | POURREZA BILANDI M. | TAGHIAN M. | Issue Writer Certificate

Keywords

HEDGINGQ2

MULTI OBJECTIVE OPTIMIZATIONQ2

RESERVOIR OPERATIONQ2

META-HEURISTIC ALGORITHMSQ2

Abstract

Multi-objective problems rarely ever provide a single optimal solution, rather they yield an optimal set of outputs (Pareto fronts). Solving these problems was previously accomplished by using some simplifier methods such as the weighting coefficient method used for converting a multi-objective problem to a single objective function. However, such robust tools as multi-objective META-HEURISTIC ALGORITHMS have been recently developed for solving these problems. The HEDGING model is one of the classic problems for RESERVOIR OPERATION that is generally employed for mitigating drought impacts in water resources management. According to this method, although it is possible to supply the total planned demands, only portions of the demands are met to save water by allowing small deficits in the current conditions in order to avoid or reduce severe deficits in future. The approach heavily depends on economic and social considerations. In the present study, the META-HEURISTIC ALGORITHMS of NSGA-II, MOPSO, SPEA-II, and AMALGAM are used toward the multi-objective optimization of the HEDGING model. For this purpose, the rationing factors involved in Taleghan dam operation are optimized over a 35-year statistical period of inflow. There are two objective functions: a) minimizing the modified shortage index, and b) maximizing the reliability index (i.e., two opposite objectives). The results show that the above algorithms are applicable to a wide range of optimal solutions. Among the algorithms, AMALGAM is found to produce a better Pareto front for the values of the objective function, indicating its more satisfactory performance.

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APA: Copy

SADEGHI TABAS, S., POURREZA BILANDI, M., & TAGHIAN, M.. (2015). MULTI-OBJECTIVE OPTIMIZATION OF THE HEDGING MODEL FOR RESERVOIR OPERATION USING EVOLUTIONARY ALGORITHMS. WATER AND WASTEWATER, 26(5 (99)), 14-22. SID. https://sid.ir/paper/103654/en

Vancouver: Copy

SADEGHI TABAS S., POURREZA BILANDI M., TAGHIAN M.. MULTI-OBJECTIVE OPTIMIZATION OF THE HEDGING MODEL FOR RESERVOIR OPERATION USING EVOLUTIONARY ALGORITHMS. WATER AND WASTEWATER[Internet]. 2015;26(5 (99)):14-22. Available from: https://sid.ir/paper/103654/en

IEEE: Copy

S. SADEGHI TABAS, M. POURREZA BILANDI, and M. TAGHIAN, “MULTI-OBJECTIVE OPTIMIZATION OF THE HEDGING MODEL FOR RESERVOIR OPERATION USING EVOLUTIONARY ALGORITHMS,” WATER AND WASTEWATER, vol. 26, no. 5 (99), pp. 14–22, 2015, [Online]. Available: https://sid.ir/paper/103654/en

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