A soft approach to supplier selection problem for a steel company under future uncertainty
الموضوعات :
1 - Khorasan Steel Complex Company, Neishabur, Razavi Khorasan.
الکلمات المفتاحية: Uncertainty, Supplier selection, decision-making, steel industry, Soft Approach,
ملخص المقالة :
The steel industry is a whole industry worldwide and a fundamental industry sector in the national economy. It is undeniable that raw materials are an essential part of a steel company's operations. Therefore, steel companies require reliable and valid raw material suppliers. One of the strategic activities of supply chain management is selecting suitable suppliers. Supplier selection (SS) is a multi-criteria decision-making process and requires a comprehensive evaluation process, often under uncertain conditions. While the application of MCDM tools is continuously growing in the SS literature, these tools can not cope with future or environmental uncertainty. The matrix approach to robustness analysis as a method capable of covering this type of uncertainty has a fundamental weakness; This approach uses only one criterion to check the performance of alternatives. This point has been considered in this study. For this purpose, a study has been conducted in a steel manufacturing company to choose the most suitable supplier among the four. Based on the proposed approach, problem owners defined future scenarios by considering different states of economic, social, and environmental variables. Then, the performance of the suppliers was judged by experts according to the cost, quality, time, supply security, and capacity criteria in the form of future scenarios. Finally, we placed the average performance of the suppliers in the five criteria in the decision matrix and prioritized them. The results showed that supplier A3 is the best option.
المصادر:
Azar, A., & Sorourkhah, A. (2015). Designing a model for three-dimensional robustness analysis: A case study of Iran Khodro machine tools industries company. Indian Journal of Science and Technology, 8(28). https://doi.org/10.17485/ijst/2015/v8i28/82447
Azimifard, A., Moosavirad, S. H., & Ariafar, S. (2018). Selecting sustainable supplier countries for Iran’s steel industry at three levels by using AHP and TOPSIS methods. Resources Policy, 57, 30–44. https://doi.org/https://doi.org/10.1016/j.resourpol.2018.01.002
Chakraborty, S., Chattopadhyay, R., & Chakraborty, S. (2020). An integrated D-MARCOS method for supplier selection in an iron and steel industry. Decision Making: Applications in Management and Engineering, 3(2), 49–69. https://doi.org/10.31181/dmame2003049c
Chutia, R., & Gogoi, M. K. (2018). Fuzzy risk analysis in poultry farming based on a novel similarity measure of fuzzy numbers. Applied Soft Computing, 66, 60–76. https://doi.org/https://doi.org/10.1016/j.asoc.2018.02.008
Dinçer, H., Yüksel, S., & Martínez, L. (2019). Interval type 2-based hybrid fuzzy evaluation of financial services in E7 economies with DEMATEL-ANP and MOORA methods. Applied Soft Computing, 79, 186–202. https://doi.org/https://doi.org/10.1016/j.asoc.2019.03.018
Edalatpanah, S. A. (2018). Neutrosophic perspective on DEA. Journal of Applied Research on Industrial Engineering, 5(4), 339–345.
Edalatpanah, S. A. (2022). Using Hesitant Fuzzy Sets to Solve the Problem of Choosing a Strategy in Uncertain Conditions. Journal of Decisions and Operations Research, 7(2), 373–382. https://doi.org/10.22105/dmor.2022.348658.1626
Engau, C., & Hoffmann, V. H. (2011). Strategizing in an unpredictable climate: exploring corporate strategies to cope with regulatory uncertainty. Long Range Planning, 44, 42–63.
Forghani, A., Sadjadi, S. J., & Farhang Moghadam, B. (2021). A Scientometric Analysis of Supplier Selection Research. Journal of Optimization in Industrial Engineering, 14(1), 149–158. https://doi.org/10.22094/joie.2021.1897173.1736
Garg, H., & Kumar, K. (2020). A novel exponential distance and its based TOPSIS method for interval-valued intuitionistic fuzzy sets using connection number of SPA theory. Artificial Intelligence Review, 53(1), 595–624. https://doi.org/10.1007/s10462-018-9668-5
Ghahremani Nahr, J., & Zahedi, M. (2021). Modeling of the supply chain of cooperative game between two tiers of retailer and manufacturer under conditions of uncertainty. International Journal of Research in Industrial Engineering, 10(2), 95–116. https://doi.org/10.22105/riej.2021.276520.1190
Ghamari, R., Mahdavi-Mazdeh, M., & Ghannadpour, S. F. (2022). Resilient and sustainable supplier selection via a new framework: a case study from the steel industry. Environment, Development and Sustainability, 24(8), 10403–10441. https://doi.org/10.1007/s10668-021-01872-5
Ghasempoor Anaraki, M., Vladislav, D. S., Karbasian, M., Osintsev, N., & Nozick, V. (2021). Evaluation and selection of supplier in supply chain with fuzzy analytical network process approach. Journal of Fuzzy Extension and Applications, 2(1), 69–88. https://doi.org/10.22105/jfea.2021.274734.1078
Goecks, L. S., dos Santosa, A. A., & Korzenowski, A. L. (2020). Decision-making trends in quality management: A literature review about industry 4.0. Production, 30. https://doi.org/10.1590/0103-6513.20190086
Hosseini-Motlagh, S.-M., Nematollahi, M., & Nouri, M. (2018). Coordination of green quality and green warranty decisions in a two-echelon competitive supply chain with substitutable products. Journal of Cleaner Production, 196, 961–984. https://doi.org/https://doi.org/10.1016/j.jclepro.2018.06.123
Jain, N., & Singh, A. R. (2020). Sustainable supplier selection criteria classification for Indian iron and steel industry: a fuzzy modified Kano model approach. International Journal of Sustainable Engineering, 13(1), 17–32. https://doi.org/10.1080/19397038.2019.1566413
Jiang, Z., Wei, G., & Guo, Y. (2022). Picture fuzzy MABAC method based on prospect theory for multiple attribute group decision making and its application to suppliers selection. Journal of Intelligent & Fuzzy Systems, 42(4), 3405–3415. https://doi.org/10.3233/jifs-211359
Kaushik, V., Kumar, A., Gupta, H., & Dixit, G. (2020). A hybrid decision model for supplier selection in Online Fashion Retail (OFR). International Journal of Logistics Research and Applications, 25(1), 1–25. https://doi.org/10.1080/13675567.2020.1791810
Kavta, K., & Goswami, A. K. (2021). A methodological framework for a priori selection of travel demand management package using fuzzy MCDM methods. Transportation, 48(6), 3059–3084.
Mahmoudi, A., Javed, S. A., & Mardani, A. (2022). Gresilient supplier selection through Fuzzy Ordinal Priority Approach: decision-making in post-COVID era. Operations Management Research, 15(1), 208–232. https://doi.org/10.1007/s12063-021-00178-z
Mallick, S. K., Rudra, S., & Samanta, R. (2020). Sustainable ecotourism development using SWOT and QSPM approach: A study on Rameswaram, Tamil Nadu. International Journal of Geoheritage and Parks, 8(3), 185–193. https://doi.org/https://doi.org/10.1016/j.ijgeop.2020.06.001
Månsson, A. (2016). Energy security in a decarbonised transport sector: A scenario based analysis of Sweden’s transport strategies. Energy Strategy Reviews, 13–14, 236–247. https://doi.org/https://doi.org/10.1016/j.esr.2016.06.004
Mao, X., Guoxi, Z., Fallah, M., & Edalatpanah, S. A. (2020). A Neutrosophic-Based Approach in Data Envelopment Analysis with Undesirable Outputs. Mathematical Problems in Engineering, 2020, 7626102. https://doi.org/10.1155/2020/7626102
Masoomi, B., Sahebi, I. G., Fathi, M., Yıldırım, F., & Ghorbani, S. (2022). Strategic supplier selection for renewable energy supply chain under green capabilities (fuzzy BWM-WASPAS-COPRAS approach). Energy Strategy Reviews, 40, 100815. https://doi.org/10.1016/j.esr.2022.100815
Maulidina, A. D., & Putra, F. E. (2018). Selection of tugboat gearbox supplier using the analytical hierarchy process method. Journal of Applied Research on Industrial Engineering, 5(3), 253–262. https://doi.org/10.22105/jarie.2018.138086.1042
Mohammad, P., & Kazemipoor, H. (2020). An integrated multi-objective mathematical model to select suppliers in green supply chains. International Journal of Research in Industrial Engineering, 9(3), 216–234. https://doi.org/10.22105/riej.2020.262937.1173
Mondal, A., & Roy, S. K. (2022). Application of Choquet integral in interval type-2 Pythagorean fuzzy sustainable supply chain management under risk. International Journal of Intelligent Systems, 37(1), 217–263. https://doi.org/10.1002/int.22623
Montibeller, G., & Franco, L. A. (2011). Raising the bar: strategic multi-criteria decision analysis. Journal of the Operational Research Society, 62(5), 855–867. https://doi.org/10.1057/jors.2009.178
Nguyen, T.-L., Nguyen, P.-H., Pham, H.-A., Nguyen, T.-G., Nguyen, D.-T., Tran, T.-H., Le, H.-C., & Phung, H.-T. (2022). A Novel Integrating Data Envelopment Analysis and Spherical Fuzzy MCDM Approach for Sustainable Supplier Selection in Steel Industry. Mathematics, 10(11), 1897. https://www.mdpi.com/2227-7390/10/11/1897
Ocampo, L. A., Himang, C. M., Kumar, A., & Brezocnik, M. (2019). A novel multiple criteria decision-making approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy AHP for mapping collection and distribution centers in reverse logistics. Advances in Production Engineering & Management, 14(3), 297–322. https://doi.org/https://doi.org/10.14743/apem2019.3.329
Oroojeni Mohammad Javad, M., Darvishi, M., & Oroojeni Mohammad Javad, A. (2020). Green supplier selection for the steel industry using BWM and fuzzy TOPSIS: A case study of Khouzestan steel company. Sustainable Futures, 2, 100012. https://doi.org/https://doi.org/10.1016/j.sftr.2020.100012
Pantha, R. P., Islam, M. S., Akter, N., & Islam, E. (2020). Sustainable supplier selection using integrated data envelopment analysis and differential evolution model. Journal of Applied Research on Industrial Engineering, 7(1), 25–35. https://doi.org/10.22105/jarie.2020.213449.1115
Ram, C., Montibeller, G., & Morton, A. (2011). Extending the use of scenario planning and MCDA for the evaluation of strategic options. Journal of the Operational Research Society, 62(5), 817–829. https://doi.org/10.1057/jors.2010.90
Rosenhead, J. (2011). Robustness Analysis. In Wiley Encyclopedia of Operations Research and Management Science. https://doi.org/10.1002/9780470400531.eorms0976
Sayyadi tooranloo, H., Karimi Takalo, S., & Mohyadini, F. (2022). Analysis of Causal Relationships Effective Factors on the Green Supplier Selection in Health Centers Using the Intuitionistic Fuzzy Cognitive Map (IFCM) Method. Journal of Optimization in Industrial Engineering, 15(1), 93–108. https://doi.org/10.22094/joie.2021.1899316.1746
Shadkam, E., Parvizi, M., & Rajabi, R. (2021). The study of multi-objective supplier selection problem by a novel hybrid method: COA/ε-constraint. International Journal of Research in Industrial Engineering, 10(3), 223–237. https://doi.org/10.22105/riej.2021.277170.1191
Shafi Salimi, P., & Edalatpanah, S. A. (2020). Supplier selection using fuzzy AHP method and D-numbers. Journal of Fuzzy Extension and Applications, 1(1), 1–14. https://doi.org/10.22105/jfea.2020.248437.1007
Shahriari, M., & pilevari, nazanin. (2016). Agile Supplier Selection In Sanitation Supply Chain Using Fuzzy VIKOR Method. Journal of Optimization in Industrial Engineering, 10(21), 19–28. https://doi.org/10.22094/joie.2016.257
Sobhanallahi, M. A., Zendehdel Nobari, N., & Pasandideh, S. H. R. (2019). An Aggregated Supplier Selection Method Based on QFD and TOPSIS (Case Study: A Financial Institution). Journal of Optimization in Industrial Engineering, 12(1), 31–40. https://doi.org/10.22094/joie.2018.721.1458
Sorourkhah, A. (2022). Coping Uncertainty in the Supplier Selection Problem Using a Scenario-Based Approach and Distance Measure on Type-2 Intuitionistic Fuzzy Sets. Fuzzy Optimization and Modeling Journal, 3(1), 64–71. https://doi.org/10.30495/fomj.2022.1953705.1066
Sorourkhah, A., Azar, A., Babaie-Kafaki, S., Shafiei-Nikabadi, M., & Author, C. (2018). Using Weighted-Robustness Analysis in Strategy Selection (Case Study: Saipa Automotive Research and Innovation Center). Industrial Management Journal, 9(4), 665–690. https://doi.org/10.22059/imj.2018.247856.1007361
Sorourkhah, A., Babaie-Kafaki, S., Azar, A., & Shafiei-Nikabadi, M. (2018). Matrix Approach to Robustness Analysis for Strategy Selection. International Journal of Industrial Mathematics, 10(3), 261–269. https://ijim.srbiau.ac.ir/article_12651_7d563b427b89b3be26549089142437dc.pdf
Sorourkhah, A., Babaie-Kafaki, S., Azar, A., & Shafiei Nikabadi, M. (2019). A Fuzzy-Weighted Approach to the Problem of Selecting the Right Strategy Using the Robustness Analysis (Case Study: Iran Automotive Industry). Fuzzy Information and Engineering, 11(1), 39–53. https://doi.org/10.1080/16168658.2021.1886811
Sorourkhah, A., & Edalatpanah, S. A. (2021a). Considering the Criteria interdependency in the Matrix Approach to Robustness Analysis with Applying Fuzzy ANP. Fuzzy Optimization and Modeling Journal, 2(2), 22–33. https://doi.org/10.30495/fomj.2021.1932066.1029
Sorourkhah, A., & Edalatpanah, S. A. (2021b). Considering the Criteria interdependency in the Matrix Approach to Robustness Analysis with Applying Fuzzy ANP. Fuzzy Optimization and …, 3(2), 22–33. http://fomj.qaemiau.ac.ir/article_683403.html
Sorourkhah, A., & Edalatpanah, S. A. (2022). Using a Combination of Matrix Approach to Robustness Analysis (MARA) and Fuzzy DEMATEL-Based ANP (FDANP) to Choose the Best Decision. International Journal of Mathematical, Engineering and Management Sciences, 7(1), 68–80. https://doi.org/https://doi.org/10.33889/IJMEMS.2022.7.1.005.
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Azar, A., & Sorourkhah, A. (2015). Designing a model for three-dimensional robustness analysis: A case study of Iran Khodro machine tools industries company. Indian Journal of Science and Technology, 8(28). https://doi.org/10.17485/ijst/2015/v8i28/82447
Azimifard, A., Moosavirad, S. H., & Ariafar, S. (2018). Selecting sustainable supplier countries for Iran’s steel industry at three levels by using AHP and TOPSIS methods. Resources Policy, 57, 30–44. https://doi.org/https://doi.org/10.1016/j.resourpol.2018.01.002
Chakraborty, S., Chattopadhyay, R., & Chakraborty, S. (2020). An integrated D-MARCOS method for supplier selection in an iron and steel industry. Decision Making: Applications in Management and Engineering, 3(2), 49–69. https://doi.org/10.31181/dmame2003049c
Chutia, R., & Gogoi, M. K. (2018). Fuzzy risk analysis in poultry farming based on a novel similarity measure of fuzzy numbers. Applied Soft Computing, 66, 60–76. https://doi.org/https://doi.org/10.1016/j.asoc.2018.02.008
Dinçer, H., Yüksel, S., & Martínez, L. (2019). Interval type 2-based hybrid fuzzy evaluation of financial services in E7 economies with DEMATEL-ANP and MOORA methods. Applied Soft Computing, 79, 186–202. https://doi.org/https://doi.org/10.1016/j.asoc.2019.03.018
Edalatpanah, S. A. (2018). Neutrosophic perspective on DEA. Journal of Applied Research on Industrial Engineering, 5(4), 339–345.
Edalatpanah, S. A. (2022). Using Hesitant Fuzzy Sets to Solve the Problem of Choosing a Strategy in Uncertain Conditions. Journal of Decisions and Operations Research, 7(2), 373–382. https://doi.org/10.22105/dmor.2022.348658.1626
Engau, C., & Hoffmann, V. H. (2011). Strategizing in an unpredictable climate: exploring corporate strategies to cope with regulatory uncertainty. Long Range Planning, 44, 42–63.
Forghani, A., Sadjadi, S. J., & Farhang Moghadam, B. (2021). A Scientometric Analysis of Supplier Selection Research. Journal of Optimization in Industrial Engineering, 14(1), 149–158. https://doi.org/10.22094/joie.2021.1897173.1736
Garg, H., & Kumar, K. (2020). A novel exponential distance and its based TOPSIS method for interval-valued intuitionistic fuzzy sets using connection number of SPA theory. Artificial Intelligence Review, 53(1), 595–624. https://doi.org/10.1007/s10462-018-9668-5
Ghahremani Nahr, J., & Zahedi, M. (2021). Modeling of the supply chain of cooperative game between two tiers of retailer and manufacturer under conditions of uncertainty. International Journal of Research in Industrial Engineering, 10(2), 95–116. https://doi.org/10.22105/riej.2021.276520.1190
Ghamari, R., Mahdavi-Mazdeh, M., & Ghannadpour, S. F. (2022). Resilient and sustainable supplier selection via a new framework: a case study from the steel industry. Environment, Development and Sustainability, 24(8), 10403–10441. https://doi.org/10.1007/s10668-021-01872-5
Ghasempoor Anaraki, M., Vladislav, D. S., Karbasian, M., Osintsev, N., & Nozick, V. (2021). Evaluation and selection of supplier in supply chain with fuzzy analytical network process approach. Journal of Fuzzy Extension and Applications, 2(1), 69–88. https://doi.org/10.22105/jfea.2021.274734.1078
Goecks, L. S., dos Santosa, A. A., & Korzenowski, A. L. (2020). Decision-making trends in quality management: A literature review about industry 4.0. Production, 30. https://doi.org/10.1590/0103-6513.20190086
Hosseini-Motlagh, S.-M., Nematollahi, M., & Nouri, M. (2018). Coordination of green quality and green warranty decisions in a two-echelon competitive supply chain with substitutable products. Journal of Cleaner Production, 196, 961–984. https://doi.org/https://doi.org/10.1016/j.jclepro.2018.06.123
Jain, N., & Singh, A. R. (2020). Sustainable supplier selection criteria classification for Indian iron and steel industry: a fuzzy modified Kano model approach. International Journal of Sustainable Engineering, 13(1), 17–32. https://doi.org/10.1080/19397038.2019.1566413
Jiang, Z., Wei, G., & Guo, Y. (2022). Picture fuzzy MABAC method based on prospect theory for multiple attribute group decision making and its application to suppliers selection. Journal of Intelligent & Fuzzy Systems, 42(4), 3405–3415. https://doi.org/10.3233/jifs-211359
Kaushik, V., Kumar, A., Gupta, H., & Dixit, G. (2020). A hybrid decision model for supplier selection in Online Fashion Retail (OFR). International Journal of Logistics Research and Applications, 25(1), 1–25. https://doi.org/10.1080/13675567.2020.1791810
Kavta, K., & Goswami, A. K. (2021). A methodological framework for a priori selection of travel demand management package using fuzzy MCDM methods. Transportation, 48(6), 3059–3084.
Mahmoudi, A., Javed, S. A., & Mardani, A. (2022). Gresilient supplier selection through Fuzzy Ordinal Priority Approach: decision-making in post-COVID era. Operations Management Research, 15(1), 208–232. https://doi.org/10.1007/s12063-021-00178-z
Mallick, S. K., Rudra, S., & Samanta, R. (2020). Sustainable ecotourism development using SWOT and QSPM approach: A study on Rameswaram, Tamil Nadu. International Journal of Geoheritage and Parks, 8(3), 185–193. https://doi.org/https://doi.org/10.1016/j.ijgeop.2020.06.001
Månsson, A. (2016). Energy security in a decarbonised transport sector: A scenario based analysis of Sweden’s transport strategies. Energy Strategy Reviews, 13–14, 236–247. https://doi.org/https://doi.org/10.1016/j.esr.2016.06.004
Mao, X., Guoxi, Z., Fallah, M., & Edalatpanah, S. A. (2020). A Neutrosophic-Based Approach in Data Envelopment Analysis with Undesirable Outputs. Mathematical Problems in Engineering, 2020, 7626102. https://doi.org/10.1155/2020/7626102
Masoomi, B., Sahebi, I. G., Fathi, M., Yıldırım, F., & Ghorbani, S. (2022). Strategic supplier selection for renewable energy supply chain under green capabilities (fuzzy BWM-WASPAS-COPRAS approach). Energy Strategy Reviews, 40, 100815. https://doi.org/10.1016/j.esr.2022.100815
Maulidina, A. D., & Putra, F. E. (2018). Selection of tugboat gearbox supplier using the analytical hierarchy process method. Journal of Applied Research on Industrial Engineering, 5(3), 253–262. https://doi.org/10.22105/jarie.2018.138086.1042
Mohammad, P., & Kazemipoor, H. (2020). An integrated multi-objective mathematical model to select suppliers in green supply chains. International Journal of Research in Industrial Engineering, 9(3), 216–234. https://doi.org/10.22105/riej.2020.262937.1173
Mondal, A., & Roy, S. K. (2022). Application of Choquet integral in interval type-2 Pythagorean fuzzy sustainable supply chain management under risk. International Journal of Intelligent Systems, 37(1), 217–263. https://doi.org/10.1002/int.22623
Montibeller, G., & Franco, L. A. (2011). Raising the bar: strategic multi-criteria decision analysis. Journal of the Operational Research Society, 62(5), 855–867. https://doi.org/10.1057/jors.2009.178
Nguyen, T.-L., Nguyen, P.-H., Pham, H.-A., Nguyen, T.-G., Nguyen, D.-T., Tran, T.-H., Le, H.-C., & Phung, H.-T. (2022). A Novel Integrating Data Envelopment Analysis and Spherical Fuzzy MCDM Approach for Sustainable Supplier Selection in Steel Industry. Mathematics, 10(11), 1897. https://www.mdpi.com/2227-7390/10/11/1897
Ocampo, L. A., Himang, C. M., Kumar, A., & Brezocnik, M. (2019). A novel multiple criteria decision-making approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy AHP for mapping collection and distribution centers in reverse logistics. Advances in Production Engineering & Management, 14(3), 297–322. https://doi.org/https://doi.org/10.14743/apem2019.3.329
Oroojeni Mohammad Javad, M., Darvishi, M., & Oroojeni Mohammad Javad, A. (2020). Green supplier selection for the steel industry using BWM and fuzzy TOPSIS: A case study of Khouzestan steel company. Sustainable Futures, 2, 100012. https://doi.org/https://doi.org/10.1016/j.sftr.2020.100012
Pantha, R. P., Islam, M. S., Akter, N., & Islam, E. (2020). Sustainable supplier selection using integrated data envelopment analysis and differential evolution model. Journal of Applied Research on Industrial Engineering, 7(1), 25–35. https://doi.org/10.22105/jarie.2020.213449.1115
Ram, C., Montibeller, G., & Morton, A. (2011). Extending the use of scenario planning and MCDA for the evaluation of strategic options. Journal of the Operational Research Society, 62(5), 817–829. https://doi.org/10.1057/jors.2010.90
Rosenhead, J. (2011). Robustness Analysis. In Wiley Encyclopedia of Operations Research and Management Science. https://doi.org/10.1002/9780470400531.eorms0976
Sayyadi tooranloo, H., Karimi Takalo, S., & Mohyadini, F. (2022). Analysis of Causal Relationships Effective Factors on the Green Supplier Selection in Health Centers Using the Intuitionistic Fuzzy Cognitive Map (IFCM) Method. Journal of Optimization in Industrial Engineering, 15(1), 93–108. https://doi.org/10.22094/joie.2021.1899316.1746
Shadkam, E., Parvizi, M., & Rajabi, R. (2021). The study of multi-objective supplier selection problem by a novel hybrid method: COA/ε-constraint. International Journal of Research in Industrial Engineering, 10(3), 223–237. https://doi.org/10.22105/riej.2021.277170.1191
Shafi Salimi, P., & Edalatpanah, S. A. (2020). Supplier selection using fuzzy AHP method and D-numbers. Journal of Fuzzy Extension and Applications, 1(1), 1–14. https://doi.org/10.22105/jfea.2020.248437.1007
Shahriari, M., & pilevari, nazanin. (2016). Agile Supplier Selection In Sanitation Supply Chain Using Fuzzy VIKOR Method. Journal of Optimization in Industrial Engineering, 10(21), 19–28. https://doi.org/10.22094/joie.2016.257
Sobhanallahi, M. A., Zendehdel Nobari, N., & Pasandideh, S. H. R. (2019). An Aggregated Supplier Selection Method Based on QFD and TOPSIS (Case Study: A Financial Institution). Journal of Optimization in Industrial Engineering, 12(1), 31–40. https://doi.org/10.22094/joie.2018.721.1458
Sorourkhah, A. (2022). Coping Uncertainty in the Supplier Selection Problem Using a Scenario-Based Approach and Distance Measure on Type-2 Intuitionistic Fuzzy Sets. Fuzzy Optimization and Modeling Journal, 3(1), 64–71. https://doi.org/10.30495/fomj.2022.1953705.1066
Sorourkhah, A., Azar, A., Babaie-Kafaki, S., Shafiei-Nikabadi, M., & Author, C. (2018). Using Weighted-Robustness Analysis in Strategy Selection (Case Study: Saipa Automotive Research and Innovation Center). Industrial Management Journal, 9(4), 665–690. https://doi.org/10.22059/imj.2018.247856.1007361
Sorourkhah, A., Babaie-Kafaki, S., Azar, A., & Shafiei-Nikabadi, M. (2018). Matrix Approach to Robustness Analysis for Strategy Selection. International Journal of Industrial Mathematics, 10(3), 261–269. https://ijim.srbiau.ac.ir/article_12651_7d563b427b89b3be26549089142437dc.pdf
Sorourkhah, A., Babaie-Kafaki, S., Azar, A., & Shafiei Nikabadi, M. (2019). A Fuzzy-Weighted Approach to the Problem of Selecting the Right Strategy Using the Robustness Analysis (Case Study: Iran Automotive Industry). Fuzzy Information and Engineering, 11(1), 39–53. https://doi.org/10.1080/16168658.2021.1886811
Sorourkhah, A., & Edalatpanah, S. A. (2021a). Considering the Criteria interdependency in the Matrix Approach to Robustness Analysis with Applying Fuzzy ANP. Fuzzy Optimization and Modeling Journal, 2(2), 22–33. https://doi.org/10.30495/fomj.2021.1932066.1029
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Sorourkhah, A., & Edalatpanah, S. A. (2022). Using a Combination of Matrix Approach to Robustness Analysis (MARA) and Fuzzy DEMATEL-Based ANP (FDANP) to Choose the Best Decision. International Journal of Mathematical, Engineering and Management Sciences, 7(1), 68–80. https://doi.org/https://doi.org/10.33889/IJMEMS.2022.7.1.005.
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