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Multi-Objective Optimal Scheduling of Generalized Water Resources Based on an Inter-Basin Water Transfer Project
For inter-basin water transfer (IBWT) projects, the conflict between social, economic, and ecological objectives makes water allocation processes more complex. Specific to the problem of water resource conflict in IBWT projects, we established an optimal allocation model of generalized (conventional) water resources (G (C) model) to demonstrate the advantages of the G model. The improved multi-objective cuckoo optimization algorithm (IMOCS) was applied to search the Pareto frontiers of the two models under normal, dry, and extremely dry conditions. The optimal allocation scheme set of generalized (conventional) water resources (G (C) scheme set) consists of ten Pareto optimal solutions with the minimum water shortage selected from the Pareto optimal solutions of the G (C) model. The analytic hierarchy process (AHP) combined with criteria importance using the inter-criteria correlation (CRITIC) method was used to assign weights of evaluation indexes in the evaluation index system. The non-negative matrix method was employed to evaluate the G (C) scheme set to determine the best G (C) scheme for the Jiangsu section of the South-to-North Water Transfer (J-SNWT) Project. The results show that (1) the Pareto frontier of the G model is better than that of the C model, and (2) the best G scheme shows better index values compared to the best C scheme. The total water shortages are reduced by 254.2 million m3 and 827.9 million m3 under the dry condition, respectively, and the water losses are reduced by 145.1 million m3 and 141.1 million m3 under the extremely dry condition, respectively. These findings could not only provide J-SNWT Project managers with guidelines for water allocation under normal, dry, and extremely dry conditions but also demonstrate that the G model could achieve better water-allocation benefits than the C model for inter-basin water transfer projects.
Multi-Objective Optimal Scheduling of Generalized Water Resources Based on an Inter-Basin Water Transfer Project
For inter-basin water transfer (IBWT) projects, the conflict between social, economic, and ecological objectives makes water allocation processes more complex. Specific to the problem of water resource conflict in IBWT projects, we established an optimal allocation model of generalized (conventional) water resources (G (C) model) to demonstrate the advantages of the G model. The improved multi-objective cuckoo optimization algorithm (IMOCS) was applied to search the Pareto frontiers of the two models under normal, dry, and extremely dry conditions. The optimal allocation scheme set of generalized (conventional) water resources (G (C) scheme set) consists of ten Pareto optimal solutions with the minimum water shortage selected from the Pareto optimal solutions of the G (C) model. The analytic hierarchy process (AHP) combined with criteria importance using the inter-criteria correlation (CRITIC) method was used to assign weights of evaluation indexes in the evaluation index system. The non-negative matrix method was employed to evaluate the G (C) scheme set to determine the best G (C) scheme for the Jiangsu section of the South-to-North Water Transfer (J-SNWT) Project. The results show that (1) the Pareto frontier of the G model is better than that of the C model, and (2) the best G scheme shows better index values compared to the best C scheme. The total water shortages are reduced by 254.2 million m3 and 827.9 million m3 under the dry condition, respectively, and the water losses are reduced by 145.1 million m3 and 141.1 million m3 under the extremely dry condition, respectively. These findings could not only provide J-SNWT Project managers with guidelines for water allocation under normal, dry, and extremely dry conditions but also demonstrate that the G model could achieve better water-allocation benefits than the C model for inter-basin water transfer projects.
Multi-Objective Optimal Scheduling of Generalized Water Resources Based on an Inter-Basin Water Transfer Project
Haichao Xi (author) / Yangyang Xie (author) / Saiyan Liu (author) / Qing Mao (author) / Teng Shen (author) / Qin Zhang (author)
2023
Article (Journal)
Electronic Resource
Unknown
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