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Fuzzy sets to model master production effectively in Make to Stock companies with Lack of Homogeneity in the Product

机译：模糊集可以有效地建模产品中缺乏同质性的按库存制造公司

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Supply chains (SCs) with Lack of Homogeneity in the Product (LHP) present inherent sources of uncertainty due to the heterogeneity of raw materials and uncontrollable productive factors. LHP SCs are characterized by producing units of the same finished goods that are not homogeneous. However, the exact quantity of each one in a production lot will only be known when it is produced. These SCs must classify finished goods into subtypes according to customer requirements. In this paper, a fuzzy mathematical programming model is proposed. To match homogeneity customer requirements with the sizing of production lots, the proposed master plan considers two main aspects: 1) forecast demand is expressed in terms of number of orders with a similar order size; 2) LHP is modeled by considering that each production lot is split into several homogeneous sub-lots. Then uncertainty is considered by means of fuzzy sets in order sizes and homogeneous sub-lots quantities. The fuzzy model is evaluated by emulating real conditions and is compared with the equivalent deterministic one to assess its robustness. The results demonstrate that the fuzzy approach outperforms the deterministic one and that it is more effective for handling real situations when LHP is present. (C) 2015 Elsevier B.V. All rights reserved.
机译：产品（LHP）缺乏同质性的供应链（SC）由于原材料的异质性和不可控制的生产要素而呈现出内在的不确定性来源。 LHP SC的特征在于，生产的同一成品的单元不是均质的。但是，只有在生产时才知道生产批次中每一个的确切数量。这些SC必须根据客户要求将制成品分类为子类型。本文提出了一种模糊数学规划模型。为了使同质性客户需求与生产批次的大小相匹配，拟议的总体计划考虑了两个主要方面：1）预测需求以具有相似订单大小的订单数量表示； 2）通过考虑将每个生产批次划分为几个同质子批次来对LHP进行建模。然后通过阶次大小和同质子批次数量的模糊集考虑不确定性。模糊模型通过仿真实际条件进行评估，并与等效确定性模型进行比较以评估其鲁棒性。结果表明，模糊方法优于确定性方法，当存在LHP时，它对于处理实际情况更有效。 （C）2015 Elsevier B.V.保留所有权利。

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