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Constructed Wetland Planning-Based Bilevel Optimization Model under Fuzzy Random Environment: Case Study of Chaohu Lake

机译:模糊随机环境下基于人工湿地规划的双层优化模型-以巢湖为例

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摘要

To optimize regional economies, social employment, and water quality protection, a multiobjective bilevel optimization model under a fuzzy random environment based on constructed wetland planning is developed in this study. Fuzzy random variables are used to describe the uncertainties in the system, and three special fuzzy random simulation methods are proposed to address the fuzzy random variable calculations. From the inherent bilevel model interaction, a new algorithm called the fuzzy random simulation-based nested genetic algorithm (FRS-based NGA) is designed as an intelligent solution to solve the model. Then, the model is applied to a real-world case: the Chaohu Lake watershed, China. The results under different objective values, probability levels, and possibility levels are compared so that an optimal scheme for regional economic development, social employment, and the wetland construction scale can be identified. Finally, the comparative analysis, sensitivity analysis, and convergence analysis are provided to illustrate the effectiveness of the proposed model and algorithm.
机译:为了优化区域经济,社会就业和水质保护,本研究建立了基于人工湿地规划的模糊随机环境下的多目标双层优化模型。用模糊随机变量来描述系统中的不确定性,并提出了三种特殊的模糊随机仿真方法来解决模糊随机变量的计算问题。从固有的双层模型交互作用出发,设计了一种新的算法,称为基于模糊随机模拟的嵌套遗传算法(基于FRS的NGA),作为求解模型的智能解决方案。然后,将该模型应用于一个实际案例:中国巢湖流域。比较了不同目标值,概率水平和可能性水平下的结果,从而可以确定区域经济发展,社会就业和湿地建设规模的最佳方案。最后,通过比较分析,敏感性分析和收敛性分析来说明所提模型和算法的有效性。

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