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An enhanced fuzzy robust optimization model for regional solid waste management under uncertainty

机译:不确定条件下区域固体废物管理的改进模糊鲁棒优化模型

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摘要

In this study, an enhanced fuzzy robust optimization (EFRO) model is proposed for supporting regional solid waste management under uncertainty. This model is an extended version of robust optimization from a stochastic to a fuzzy environment, and novel in the following two aspects: (1) it uses multiple algorithms to tackle fuzzy constraints according to their characteristics; and (2) it incorporates fuzzy violation variables into the model, which could effectively reflect the trade-off between system economy and reliability. The regional waste management of the City of Dalian, China, was used as a case study for demonstration. A variety of solutions was obtained under various weight coefficients and confidence levels. From the case study, it was found that EFRO could help decision makers to design desired waste management alternatives under complex uncertainties. The successful application of EFRO in the studied real case is expected to be a good example for solid waste management in many other cities.
机译:在这项研究中,提出了一种增强的模糊鲁棒优化(EFRO)模型来支持不确定性下的区域固体废物管理。该模型是从随机环境到模糊环境的鲁棒优化的扩展版本,在以下两个方面具有新颖性:(1)它使用多种算法根据模糊约束的特征进行处理; (2)将模糊违规变量纳入模型,可以有效反映系统经济性与可靠性之间的权衡。以中国大连市的区域废物管理为例进行了演示。在各种权重系数和置信度下获得了各种解决方案。从案例研究中发现,EFRO可以帮助决策者在复杂的不确定性下设计所需的废物管理替代方案。 EFRO在实际案例研究中的成功应用有望成为许多其他城市固体废物管理的典范。

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