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Fuzzy optimization of units products in mix-product selection problem using fuzzy linear programming approach

机译:基于模糊线性规划的混合产品选择问题中单位产品的模糊优化

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In this paper, the modified S-curve membership function methodology is used in a real life industrial problem of mix product selection. This problem occurs in the production planning management where by a decision maker plays important role in making decision in an uncertain environment. As analysts, we try to find a good enough solution for the decision maker to make a final decision. An industrial application of fuzzy linear programming (FLP) through the S-curve membership function has been investigated using a set of real life data collected from a Chocolate Manufacturing Company. The problem of fuzzy product mix selection has been defined. The objective of this paper is to find an optimal units of products with higher level of satisfaction with vagueness as a key factor. Since there are several decisions that were to be taken, a table for optimal units of products respect to vagueness and degree of satisfaction has been defined to identify the solution with higher level of units of products and with a higher degree of satisfaction. The fuzzy outcome shows that higher units of products need not lead to higher degree of satisfaction. The findings of this work indicates that the optimal decision is depend on vagueness factor in the fuzzy system of mix product selection problem. Further more the high level of units of products obtained when the vagueness is low.
机译:本文将改进的S曲线隶属度函数方法用于混合产品选择的现实工业问题。这个问题发生在生产计划管理中,决策者在不确定的环境中做出决策时起着重要作用。作为分析师,我们试图为决策者找到一个足够好的解决方案以做出最终决定。通过使用从巧克力制造公司收集的一组现实生活数据,研究了通过S曲线隶属函数进行模糊线性规划(FLP)的工业应用。定义了模糊的产品组合选择问题。本文的目的是找到对模糊性较高的满意程度较高的最佳产品单元。由于要做出多个决定,因此已定义了关于模糊性和满意度的最佳产品单位表,以识别具有较高水平的产品单位和较高满意度的解决方案。模糊的结果表明,较高的产品单位不一定会导致较高的满意度。这项工作的结果表明,最优决策取决于模糊产品的混合产品选择问题。当模糊性较低时,所获得的产品单位量更高。

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