3) A robot vakuum cleaner factory has decided to classify its inventories through multicriteria ABC analysis considering

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3) A robot vakuum cleaner factory has decided to classify its inventories through multicriteria ABC analysis considering

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3 A Robot Vakuum Cleaner Factory Has Decided To Classify Its Inventories Through Multicriteria Abc Analysis Considering 1
3 A Robot Vakuum Cleaner Factory Has Decided To Classify Its Inventories Through Multicriteria Abc Analysis Considering 1 (60.43 KiB) Viewed 114 times
3) A robot vakuum cleaner factory has decided to classify its inventories through multicriteria ABC analysis considering its inherent uncertainties. The inventories are evaluated based on several criteria which are identified as Monetary value (CI), Storage space (C2) and Lead time (C3). In the analysis, initially the criteria weights will be computed through fuzzy AHP method. Pairwise comparison judgments are collected from experts using a linguistic scale. Then, the linguistic evaluations are converted to their corresponding triangular fuzzy numbers as in Table 1. a) Calculate the priorities of the criteria using Chang's fuzzy AHP method. Pairwise comparison matrix of criteria Criteria C2 C3 C1: Monetary value (1, 1, 1) (1.0, 1.5, 2.0) C2: Storage space (1, 1, 1) (1.0, 1.5, 2.0) C3: Lead time (1, 1, 1) CI The triangular fuzzy number of * based on student IDs Sum of the numbers in your student ID 10-18 (0.50, 0.67, 1) 19-25 (1.5, 2, 2.5) 26-35 (1, 1.5, 2) The judgment expressed with varies depending on student IDs. For instance, if your student ID is 11920307 (the sum of the numbers makes 23), so the fuzzy number of (1.5, 2, 2.5) should be substituted with (Note: the consistency of the pairwise comparison matrix is checked for all possible • values.)
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