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A Fuzzy Supplier Selection Application Using Large Survey Datasets of Delivery Performance

机译:使用大型交付绩效调查数据集的模糊供应商选择应用程序

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A model is developed using fuzzy probability to screen survey data across relevant criteria for selecting suppliers based on fuzzy expected values. The values are derived from qualitative variables and expert opinion of membership in these variables found in industry survey data. The application is made to a supply chain management decision of supplier selection based upon delivery performance which is further divided into attributes that comprise this criterion. The algorithm allows multiple criteria to be considered for each decision parameter. Large sets of survey data regarding six suppliers in the electronic parts industry are gathered from over 150 purchasers and are analyzed through spreadsheet modeling of the fuzzy algorithm. The resulting decision support system allows supply chain managers to improve supplier selection decisions by applying fuzzy measures of criteria and associated beliefs across the dataset. The proposed model and method are highly adaptable to existing survey datasets, including datasets that have incomplete data, and can be implemented in organizations with low decision support resources, such as small and medium sized organizations.
机译:使用模糊概率开发模型,以根据相关标准筛选调查数据,以基于模糊期望值选择供应商。这些值是从定性变量和行业调查数据中这些变量的成员资格专家意见中得出的。基于交付绩效对供应商选择的供应链管理决策进行了应用,该交付绩效进一步分为构成该标准的属性。该算法允许为每个决策参数考虑多个标准。从150多个采购商那里收集了有关电子零件行业中六个供应商的大量调查数据,并通过模糊算法的电子表格建模对其进行了分析。最终的决策支持系统允许供应链管理者通过在整个数据集中应用标准和相关信念的模糊度量来改善供应商选择决策。所提出的模型和方法高度适用于现有的调查数据集,包括数据不完整的数据集,并且可以在决策支持资源较低的组织(如中小型组织)中实施。

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