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Robust Fully Fuzzy Programming with Fuzzy Set Ranking Method for Environmental Systems Planning Under Uncertainty

机译:不确定环境系统规划的鲁棒全模糊规划与模糊集排序法

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摘要

This article proposes a new robust interactive interval fully fuzzy linear programming (RIIFFLP) method, using the fuzzy ranking method to find a balance between the requirements of constraints and the objective function of a fuzzy set function, as a technique for optimal decision-making under uncertainty. It considerably improved previous interval fuzzy linear programming (FLP) methods by using a new solution method named the robust two-step method (RTSM). The RTSM has a higher membership degree for the fuzzy subset, which allows interval results to stay within the boundaries of constraints. This RIIFFLP model was applied to a case study in municipal solid waste management. Results demonstrated that the solution obtained from the RIIFFLP model had more feasible results by comparison with existing FLP methods. The RIIFFLP also provided optimal interval solutions in different α levels that made decision making easier by simply choosing a suitable scenario. Therefore, the RIIFFLP model can be considered a better practical method for problem-solving when uncertainties are present.
机译:本文提出了一种新的鲁棒交互式区间完全模糊线性规划(RIIFFLP)方法,该方法使用模糊排序方法来找到约束的要求与模糊集函数的目标函数之间的平衡,以此作为优化决策的一种技术。不确定。通过使用一种称为鲁棒两步法(RTSM)的新解决方法,它大大改进了以前的区间模糊线性规划(FLP)方法。 RTSM对模糊子集具有较高的隶属度,从而使区间结果保持在约束范围内。该RIIFFLP模型已应用于城市固体废物管理的案例研究。结果表明,与现有的FLP方法相比,从RIIFFLP模型获得的解具有更可行的结果。 RIIFFLP还提供了不同α级别的最佳区间解决方案,只需选择合适的方案即可简化决策。因此,当存在不确定性时,RIIFFLP模型可以被认为是解决问题的一种更好的实用方法。

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