Application of interval multi-objective fuzzy programming based on uncertainty in optimal allocation of water resources
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Abstract:
Based on the principles of multi-objective planning, fuzzy planning and interval planning, with the goal of maximizing economic, social and environmental benefits, and taking water demand, water availability and water fairness between water departments in different sub-districts as the main constraints, a multi-objective fuzzy planning model based on uncertainty suitable for multiple water sources, multiple sub-areas and multiple users is constructed, and strives to balance the amount of user-allocated water in the water resources allocation system. The relationship between water shortage risk and system benefits maximizes the comprehensive benefits of the system. The model transforms the multi-objective program into a single-objective program by introducing a fuzzy membership function and using a two-step interactive algorithm. The model is also applied to the optimal allocation of water resources in Hengshui City, Hebei Province, and an optimal water allocation plan for 11 sub-areas, four water sources and four water consuming industries is obtained for the planning level in 2020. The results indicate that the method can be used to study the optimal allocation of water resources between multi-source, multi-area, and multi-water sectors. The optimal model achieves complementarity between multiple water sources and multiple objectives, and provides a decision-making basis for optimal allocation of water resources in arid and water-deficient areas. At the same time, after considering the fairness constraint of water use, under the condition of water shortage, the flow of water resources to regions and sectors with high unilateral water efficiency can be effectively controlled, which is conducive to multi-regional and multi-sectoral sharing of water shortage risks. The research results can provide technical reference for the optimal allocation of water resources in other counties in Hebei Province.
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