RAGA-FAHP Based Decision-Making Model for Normal High Water Level of a Reservoir

The decision-making of normal high water level of a reservoir is a complex and uncertainty problem. To avoid the qualitative and subjective defects of traditional decision-making methods, a novel method by means of fuzzy analytic hierarchy process (FAHP) combined with real coding based accelerating genetic algorithm (RAGA), is described in this paper. A fuzzy preferential relation matrix is established with the pairwise comparison of schemes for evaluation indexes. The consistency index coefficient (CIC) of optimum value satisfied with the minimizing condition is calculated by means of RAGA. Moreover, the best preference scheme is selected according to maximum subordination principle of general optimum value. Finally, a case is given to show the feasibility and effectiveness of this proposed model. The results from the application and comparison with the tradition FHAP method show that this proposed model used to optimize normal high water level of a reservoir is effective and objective and easy to operate.