Academia.eduAcademia.edu

Figure 1 – uploaded by Mohsen Anvari

See full PDFdownloadDownload figure
Table 1. Definition and membership function of Linguistic Terms eigenvalue of the comparison matrix, n is the dimension of the matrix, and the inconsistency index of the random matrix(IIR) is selected from Table 2 (Saaty,1994; Saaty, 2000; Kwong and Bai, 2010). Step - 3 Defuzzification

Table 1 Definition and membership function of Linguistic Terms eigenvalue of the comparison matrix, n is the dimension of the matrix, and the inconsistency index of the random matrix(IIR) is selected from Table 2 (Saaty,1994; Saaty, 2000; Kwong and Bai, 2010). Step - 3 Defuzzification

Related Figures (17)

EVALUATING SCOR METRICS OF SUPPLY CHAIN »>9ERFORMANCE BASED ON INVENTORY MANAGEMENT
EVALUATING SCOR METRICS OF SUPPLY CHAIN »>9ERFORMANCE BASED ON INVENTORY MANAGEMENT
Figure 1. Proposed FAHP Model for SCOR Metrics of SCP based on Inventory Management
Figure 1. Proposed FAHP Model for SCOR Metrics of SCP based on Inventory Management
Figure 2. Fuzzy AHP flowchart
Figure 2. Fuzzy AHP flowchart
In this article, 9-point TFNs (1,2,3,...,9) are used for constructing a pairwise comparison matrix. The 9 TFNs are defined with the related triangular fuzzy sets, as shown in Figure 4 and Table 1 (Saaty, 2000).
In this article, 9-point TFNs (1,2,3,...,9) are used for constructing a pairwise comparison matrix. The 9 TFNs are defined with the related triangular fuzzy sets, as shown in Figure 4 and Table 1 (Saaty, 2000).
company criteria are ranked second and _ third respectively. Table 4. Final weights of Inventory Management factors As evident in Table 3, all the fuzzy numbers of the aggregated questionnaire of the experts in the pairwise comparison of Inventory Management factors have been calculated through the geometric mean. The fuzzy weights of Inventory Management factors are shown in Table 4. After preparing the pairwise comparison questionnaire and obtaining SCOR through 15 experts in the industry, Aggregation of questionnaires (using the geometric Table 3. Aggregation of experts’ opinions of criteria (geometr
company criteria are ranked second and _ third respectively. Table 4. Final weights of Inventory Management factors As evident in Table 3, all the fuzzy numbers of the aggregated questionnaire of the experts in the pairwise comparison of Inventory Management factors have been calculated through the geometric mean. The fuzzy weights of Inventory Management factors are shown in Table 4. After preparing the pairwise comparison questionnaire and obtaining SCOR through 15 experts in the industry, Aggregation of questionnaires (using the geometric Table 3. Aggregation of experts’ opinions of criteria (geometr
Step 2 - Pairwise comparisons of SCM indicators. The SCOR ranking (Reliability, Responsiveness, Agility, Cost, and Asset) is based on the criteria of Inventory Management (product, company, supplier) presented in Table 5. Based on this model, pairwise comparisons of 5 alternatives (Supply Chain Performance indicators) are performed in three stages based on three Inventory Management criteria (product, company, supplier) separately. Carrying out this process for each of the criteria is in four steps:
Step 2 - Pairwise comparisons of SCM indicators. The SCOR ranking (Reliability, Responsiveness, Agility, Cost, and Asset) is based on the criteria of Inventory Management (product, company, supplier) presented in Table 5. Based on this model, pairwise comparisons of 5 alternatives (Supply Chain Performance indicators) are performed in three stages based on three Inventory Management criteria (product, company, supplier) separately. Carrying out this process for each of the criteria is in four steps:
Table 7. The geometric mean of Alternatives based on product criteria Table 8. Fuzzy weights of Alternatives based on product criteria The final weights of SCM alternatives based on product criteria are shown in Table 9.
Table 7. The geometric mean of Alternatives based on product criteria Table 8. Fuzzy weights of Alternatives based on product criteria The final weights of SCM alternatives based on product criteria are shown in Table 9.
Table 11. Final weights of Alternatives based on Company criteria According to the results from the company criteria, agility is more important, and reliability is ranked second. In the following, after calculating the“geometric mean” and “fuzzy weight” of the alternative options based on the company criteria, the final weights of the alternatives based on the company criteria are calculated.
Table 11. Final weights of Alternatives based on Company criteria According to the results from the company criteria, agility is more important, and reliability is ranked second. In the following, after calculating the“geometric mean” and “fuzzy weight” of the alternative options based on the company criteria, the final weights of the alternatives based on the company criteria are calculated.
Table 9. Final weights of Alternatives based on product criteria According to Table 9, the final ranking of Supply Chain Performance alternatives based on the criterion of the product will be as follows: 1-Agility, 2-Responsiveness, 3-Reliability, 4-Asset, 5-Cost.
Table 9. Final weights of Alternatives based on product criteria According to Table 9, the final ranking of Supply Chain Performance alternatives based on the criterion of the product will be as follows: 1-Agility, 2-Responsiveness, 3-Reliability, 4-Asset, 5-Cost.
Figure 5. Final ranking of alternatives based on their weights After determining the IR (less than 0.1), the questionnaires are consistent according to Table 12 and are suitable for analysis. In the following, after calculating the “geometric mean” and “fuzzy weight” of the alternative options based on the company criteria, the final weights of the alternatives based on the Supplier criteria are calculated in Table 13.
Figure 5. Final ranking of alternatives based on their weights After determining the IR (less than 0.1), the questionnaires are consistent according to Table 12 and are suitable for analysis. In the following, after calculating the “geometric mean” and “fuzzy weight” of the alternative options based on the company criteria, the final weights of the alternatives based on the Supplier criteria are calculated in Table 13.
Table 13. Final weights of Alternatives based on Supplier criteria Based on the numbers obtained in table 12, it is clear that all the fuzzy numbers of the aggregated questionnaire of the experts in the pairwise comparison of the Supply Chain Performance alternatives were calculated based on the criteria of the supplier (inventory) through the geometric mean, and the numbers below the main diameter are inversed numbers above the main diameter.
Table 13. Final weights of Alternatives based on Supplier criteria Based on the numbers obtained in table 12, it is clear that all the fuzzy numbers of the aggregated questionnaire of the experts in the pairwise comparison of the Supply Chain Performance alternatives were calculated based on the criteria of the supplier (inventory) through the geometric mean, and the numbers below the main diameter are inversed numbers above the main diameter.
different criteria, only the first and last tables have been given.
different criteria, only the first and last tables have been given.
By varying the weights of two criteria, which resulted in three scenarios, various scenarios were represented to investigate the impact of weights on selecting five alternatives. The weights of criteria 1 and 2 are switched in each experiment as indicated by the C12 symbol, which denotes the weight switch. Table 16 and Figure 6 Table 16. Results of sensitivity analysis Figure 6. Sensitivity analysis in a radar chart present the sensitivity analysis results, showing that A3 scored highest twice and Al ranked first once in the three experiments. The outcome demonstrates the robustness and low sensitivity of the criteria. As a result, the decision-making process rarely responds to the weight of the criteria.
By varying the weights of two criteria, which resulted in three scenarios, various scenarios were represented to investigate the impact of weights on selecting five alternatives. The weights of criteria 1 and 2 are switched in each experiment as indicated by the C12 symbol, which denotes the weight switch. Table 16 and Figure 6 Table 16. Results of sensitivity analysis Figure 6. Sensitivity analysis in a radar chart present the sensitivity analysis results, showing that A3 scored highest twice and Al ranked first once in the three experiments. The outcome demonstrates the robustness and low sensitivity of the criteria. As a result, the decision-making process rarely responds to the weight of the criteria.
Related topics:
Supply Chain ManagementPetrochemical industrySupply Chain Performance Management
580 California St., Suite 400
San Francisco, CA, 94104
© 2025 Academia. All rights reserved