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Managing demand uncertainty through fuzzy inference in supply chain planning

机译:在供应链计划中通过模糊推理来管理需求不确定性

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In this paper, we investigate methods for managing the irregular and uncertain demands involved in supply chain planning. We first build a supply chain planning model based on fuzzy linear programming, which defines demand as a fuzzy parameter. Next, we propose a fuzzy inference approach for converting fuzzy demand into crisp demand. In the proposed fuzzy inference-based approach, judgments of upcoming demand from both internal and external experts are used as input variables to reflect the expected demand irregularity. By adopting fuzzy inference, we can compensate for the limitations of the existing demand treatment approaches, which usually demonstrate poor forecasting performance in cases of irregular demand and thus reduce the accuracy of supply chain planning. To verify the feasibility of the proposed approach, we present an illustrative example of a Korean electronics company.
机译:在本文中,我们研究了用于管理供应链计划中不规则和不确定需求的方法。我们首先建立基于模糊线性规划的供应链计划模型,该模型将需求定义为模糊参数。接下来,我们提出了一种将模糊需求转换为清晰需求的模糊推理方法。在提出的基于模糊推理的方法中,内部和外部专家对即将到来的需求的判断被用作输入变量,以反映预期的需求不规则性。通过采用模糊推理,我们可以弥补现有需求处理方法的局限性,这些需求处理方法通常在需求不规则的情况下显示出较差的预测性能,从而降低了供应链计划的准确性。为了验证该方法的可行性,我们以一家韩国电子公司为例进行说明。

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