How to cite this paper
Chawla, V., Itika, I., Singh, P & Singh, S. (2024). A fuzzy Pythagorean TODIM method for sustainable ABC analysis in inventory management.Journal of Future Sustainability, 4(2), 85-100.
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Ali, A., Soni, M., Javaid, M., & Haleem, A. (2020). A comparative analysis of different rapid prototyping techniques for making intricately shaped structure. Journal of Industrial Integration and Management, 5(03), 393-407.
Antosz, K., & Ratnayake, R. C. (2016). Classification of spare parts as the element of a proper realization of the ma-chine maintenance process and logistics-case study. IFAC-PapersOnLine, 49(12), 1389-1393.
Atanassov, K. T. (1994). New operations defined over the intuitionistic fuzzy sets. Fuzzy sets and Systems, 61(2), 137-142.
Behzadian, M., Kazemzadeh, R. B., Albadvi, A., & Aghdasi, M. (2010). PROMETHEE: A comprehensive literature re-view on methodologies and applications. European journal of Operational research, 200(1), 198-215.
Braglia, M., Grassi, A., & Montanari, R. (2004). Multi‐attribute classification method for spare parts inventory man-agement. Journal of quality in maintenance engineering, 10(1), 55-65.
Büyüközkan, G., & Çifçi, G. (2012). A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers. Expert Systems with Applications, 39(3), 3000-3011.
Celik, E., Gumus, A. T., & Alegoz, M. (2014). A trapezoidal type-2 fuzzy MCDM method to identify and evaluate criti-cal success factors for humanitarian relief logistics management. Journal of Intelligent & Fuzzy Systems, 27(6), 2847-2855.
Chanda, A. K., Chawla, V. K., & Angra, S. K. (2018). A modified memetic particle swarm optimization algorithm for sustainable multi-objective scheduling of automatic guided vehicles in a flexible manufacturing sys-tem. International Journal of Computer Aided Manufacturing, 4(1), 33-47.
Chawla, V. K., Chanda, A. K., & Angra, S. (2019a). Automatic guided vehicle systems in flexible manufacturing sys-tem–A review. International Journal of Industrial Engineering: Theory, Applications and Practice, 26(5).
Chawla, V. K., Chanda, A. K., Angra, S., & Rani, S. (2019b). Effect of nature-inspired algorithms and hybrid dispatch-ing rules on the performance of automatic guided vehicles in the flexible manufacturing system. Journal of the Bra-zilian Society of Mechanical Sciences and Engineering, 41, 1-17.
Chawla, V. K., Chhabra, D., Gupta, P., & Naaz, S. (2021). Evaluation of green operations management by fuzzy analyti-cal hierarchy process. Materials Today: Proceedings, 38, 274-279.
Chawla, V., Angra, S., Suri, S., & Kalra, R. (2020). A synergic framework for cyber-physical production systems in the context of industry 4.0 and beyond. International Journal of Data and Network Science, 4(2), 237-244.
Chawla, V., Chanda, A., & Angra, S. (2018). Sustainable multi-objective scheduling for automatic guided vehicle and flexible manufacturing system by a grey wolf optimization algorithm. International Journal of Data and Network Science, 2(1), 27-40.
Chawla, V., Chanda, A., & Angra, S. (2019c). Material handling robots fleet size optimization by a heuristic. Journal of Project Management, 4(3), 177-184.
de Paula Vidal, G. H., Caiado, R. G. G., Scavarda, L. F., Ivson, P., & Garza-Reyes, J. A. (2022). Decision support framework for inventory management combining fuzzy multicriteria methods, genetic algorithm, and artificial neu-ral network. Computers & Industrial Engineering, 174, 108777.
Diaby, V., Campbell, K., & Goeree, R. (2013). Multi-criteria decision analysis (MCDA) in health care: a bibliometric analysis. Operations Research for Health Care, 2(1-2), 20-24.
Dodgson, J. S., Spackman, M., Pearman, A., & Phillips, L. D. (2009). Multi-criteria analysis: a manual.
Dwivedi, P., Siddiquee, A. N., & Maheshwari, S. (2021). Issues and requirements for aluminum alloys used in aircraft components: state of the art. Russian Journal of Non-Ferrous Metals, 62, 212-225.
Fan, Z. P., Zhang, X., Chen, F. D., & Liu, Y. (2013). Extended TODIM method for hybrid multiple attribute decision making problems. Knowledge-Based Systems, 42, 40-48.
Ghorabaee, M. K., Zavadskas, E. K., Amiri, M., & Turskis, Z. (2016). Extended EDAS method for fuzzy multi-criteria decision-making: an application to supplier selection. International journal of computers communications & con-trol, 11(3), 358-371.
Gomes, L. F. A. M., & Lima, M. M. P. P. (1991). TODIMI: Basics and application to multicriteria ranking. Found. Comput. Decis. Sci, 16(3-4), 1-16.
Gomes, L. F. A. M., Rangel, L. A. D., & Maranhão, F. J. C. (2009). Multicriteria analysis of natural gas destination in Brazil: An application of the TODIM method. Mathematical and Computer Modelling, 50(1-2), 92-100.
Gupta, P., Chawla, V., Jain, V., & Angra, S. (2022). Green operations management for sustainable development: An ex-plicit analysis by using fuzzy best-worst method. Decision Science Letters, 11(3), 357-366.
Hadi-Vencheh, A., & Mohamadghasemi, A. (2011). A fuzzy AHP-DEA approach for multiple criteria ABC inventory classification. Expert Systems with Applications, 38(4), 3346-3352.
Hayashi, K. (2000). Multicriteria analysis for agricultural resource management: a critical survey and future perspec-tives. European journal of operational research, 122(2), 486-500.
Huang, J. J., Tzeng, G. H., & Liu, H. H. (2009). A revised VIKOR model for multiple criteria decisions making-The per-spective of regret theory. In Cutting-Edge Research Topics on Multiple Criteria Decision Making: 20th Internation-al Conference, MCDM 2009, Chengdu/Jiuzhaigou, China, June 21-26, 2009. Proceedings (pp. 761-768). Springer Berlin Heidelberg.
Huang, J., Li, Z. S., & Liu, H. C. (2017). New approach for failure mode and effect analysis using linguistic distribution assessments and TODIM method. Reliability Engineering & System Safety, 167, 302-309.
Kaabi, H., Jabeur, K., & Ladhari, T. (2018). A genetic algorithm-based classification approach for multicriteria ABC analysis. International Journal of Information Technology & Decision Making, 17(06), 1805-1837.
Kahraman, C., Keshavarz Ghorabaee, M., Zavadskas, E. K., Cevik Onar, S., Yazdani, M., & Oztaysi, B. (2017). Intui-tionistic fuzzy EDAS method: an application to solid waste disposal site selection. Journal of Environmental Engi-neering and Landscape Management, 25(1), 1-12.
Kaur, P., Pradhan, B. L., & Priya, A. (2022). TODIM approach for selection of inventory policy in supply chain. Mathematical Problems in Engineering, 2022.
Li, M., Wu, C., Zhang, L., & You, L. N. (2015). An intuitionistic fuzzy-TODIM method to solve distributor evaluation and selection problem. International Journal of Simulation Modelling, 14(3), 511-524.
Liang, D., Zhang, Y., Xu, Z., & Jamaldeen, A. (2019). Pythagorean fuzzy VIKOR approaches based on TODIM for eval-uating internet banking website quality of Ghanaian banking industry. Applied soft computing, 78, 583-594.
Mulliner, E., Malys, N., & Maliene, V. (2016). Comparative analysis of MCDM methods for the assessment of sustain-able housing affordability. Omega, 59, 146-156.
Naeini, A. B., Mojaradi, B., Zamani, M., & Chawla, V. K. (2019). Prevention of cardiovascular diseases by combining GIS with fuzzy best-worst decision-making algorithm in areas of Tehran. International Journal of Industrial Engi-neering and Production Research, 30(3), 255-271.
Opricovic, S. (2016). A comparative analysis of the DEA-CCR model and the VIKOR method. Yugoslav Journal of Op-erations Research, 18(2).
Opricovic, S., & Tzeng, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European journal of operational research, 156(2), 445-455.
Parashar, S., & Chawla, V. (2023). Kenaf-Coir based hybrid nano-composite: an analytical and representative volume element analysis. Engineering Solid Mechanics, 11(1), 103-118.
Parashar, S., & Chawla, V. K. (2021). A systematic review on sustainable green fibre reinforced composite and their an-alytical models. Materials Today: Proceedings, 46, 6541-6546.
Partovi, F. Y., & Anandarajan, M. (2002). Classifying inventory using an artificial neural network approach. Computers & Industrial Engineering, 41(4), 389-404.
Partovi, F. Y., & Burton, J. (1993). Using the analytic hierarchy process for ABC analysis. International Journal of Op-erations & Production Management.
Pol, A., Malagi, R., & Munshi, G. (2022). Identification of mechanical properties of an araldite LY556 blended with DNR composite and polyacetal: A comparative study for sustainable future. Journal of Future Sustainability, 2(4), 149-156.
Rabbani, A., Zamani, M., Yazdani-Chamzini, A., & Zavadskas, E. K. (2014). Proposing a new integrated model based on sustainability balanced scorecard (SBSC) and MCDM approaches by using linguistic variables for the perfor-mance evaluation of oil producing companies. Expert systems with applications, 41(16), 7316-7327.
Rahman, M. Z., Siddiquee, A. N., Khan, Z. A., & Ahmad, S. (2022). Multi-response optimization of FSP parameters on mechanical properties of surface composite. Materials Today: Proceedings, 62, 5-8.
Rauf, M., Guan, Z., Sarfraz, S., Mumtaz, J., Almaiman, S., Shehab, E., & Jahanzaib, M. (2018, September). Multi-criteria inventory classification based on multi-criteria decision-making (MCDM) technique. In Advances in Manu-facturing Technology XXXII: Proceedings of the 16th International Conference on Manufacturing Research, incor-porating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden (Vol. 8, p. 343). IOS Press.
Ren, L., Zhang, Y., Wang, Y., & Sun, Z. (2007). Comparative analysis of a novel M-TOPSIS method and TOP-SIS. Applied Mathematics Research eXpress, 2007.
Sadjadi, S. (2021). A survey on the effect of plastic pollution in the Great Lakes. Journal of Future Sustainability, 1(1), 5-8.
Sadjadi, S. S., & Ghaderi, S. F. (2023). The role of interest rate and inflation on oil stock prices: Evidence from Ukraine-Russia war. Journal of Industrial and Systems Engineering, 14(4), 174-181.
Sánchez-Lozano, J. M., Teruel-Solano, J., Soto-Elvira, P. L., & García-Cascales, M. S. (2013). Geographical Infor-mation Systems (GIS) and Multi-Criteria Decision Making (MCDM) methods for the evaluation of solar farms loca-tions: Case study in south-eastern Spain. Renewable and sustainable energy reviews, 24, 544-556.
Saxena, T., & Chawla, V. K. (2021). Banana leaf fiber-based green composite: An explicit review report. Materials To-day: Proceedings, 46, 6618-6624.
Saxena, T., & Chawla, V. K. (2022). Evaluation of mechanical properties for banana-carbon fiber reinforced nano-clay epoxy composite using analytical modeling and simulation. Research on Engineering Structures and Materials, 8(4), 773-798.
Shyur, H. J., & Shih, H. S. (2006). A hybrid MCDM model for strategic vendor selection. Mathematical and computer modelling, 44(7-8), 749-761.
Touni, Z., Makui, A., & Mohammadi, E. (2019). A MCDM-based approach using UTA-STRAR method to discover behavioral aspects in stock selection problem. International Journal of Industrial Engineering and Production Research, 30(1), 93-103.
Van den Berg, J. P., & Zijm, W. H. (1999). Models for warehouse management: Classification and exam-ples. International journal of production economics, 59(1-3), 519-528.
Wang, P., Zhu, Z., & Wang, Y. (2016). A novel hybrid MCDM model combining the SAW, TOPSIS and GRA methods based on experimental design. Information Sciences, 345, 27-45.
Wang, S., & Liu, J. (2017). Extension of the TODIM method to intuitionistic linguistic multiple attribute decision making. Symmetry, 9(6), 95.
Wu, Q., Lin, W., Zhou, L., Chen, Y., & Chen, H. (2019). Enhancing multiple attribute group decision making flexibility based on information fusion technique and hesitant Pythagorean fuzzy sets. Computers & Industrial Engineer-ing, 127, 954-970.
Yadav, E., & Chawla, V. K. (2022a). An explicit literature review on bearing materials and their defect detection tech-niques. Materials Today: Proceedings, 50, 1637-1643.
Yadav, E., & Chawla, V. K. (2022b). Fault detection in rotating elements by using fuzzy integrated improved local bina-ry pattern method. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 44(12), 596.
Yager, R. R., & Abbasov, A. M. (2013). Pythagorean membership grades, complex numbers, and decision mak-ing. International Journal of Intelligent Systems, 28(5), 436-452.
Zadeh, L. (1965). Fuzzy sets. Inform Control, 8, 338-353.
Zanakis, S. H., Solomon, A., Wishart, N., & Dublish, S. (1998). Multi-attribute decision making: A simulation compari-son of select methods. European journal of operational research, 107(3), 507-529.
Zavadskas, E. K., Mardani, A., Turskis, Z., Jusoh, A., & Nor, K. M. (2016). Development of TOPSIS method to solve complicated decision-making problems—An overview on developments from 2000 to 2015. International Journal of Information Technology & Decision Making, 15(03), 645-682.
Antosz, K., & Ratnayake, R. C. (2016). Classification of spare parts as the element of a proper realization of the ma-chine maintenance process and logistics-case study. IFAC-PapersOnLine, 49(12), 1389-1393.
Atanassov, K. T. (1994). New operations defined over the intuitionistic fuzzy sets. Fuzzy sets and Systems, 61(2), 137-142.
Behzadian, M., Kazemzadeh, R. B., Albadvi, A., & Aghdasi, M. (2010). PROMETHEE: A comprehensive literature re-view on methodologies and applications. European journal of Operational research, 200(1), 198-215.
Braglia, M., Grassi, A., & Montanari, R. (2004). Multi‐attribute classification method for spare parts inventory man-agement. Journal of quality in maintenance engineering, 10(1), 55-65.
Büyüközkan, G., & Çifçi, G. (2012). A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers. Expert Systems with Applications, 39(3), 3000-3011.
Celik, E., Gumus, A. T., & Alegoz, M. (2014). A trapezoidal type-2 fuzzy MCDM method to identify and evaluate criti-cal success factors for humanitarian relief logistics management. Journal of Intelligent & Fuzzy Systems, 27(6), 2847-2855.
Chanda, A. K., Chawla, V. K., & Angra, S. K. (2018). A modified memetic particle swarm optimization algorithm for sustainable multi-objective scheduling of automatic guided vehicles in a flexible manufacturing sys-tem. International Journal of Computer Aided Manufacturing, 4(1), 33-47.
Chawla, V. K., Chanda, A. K., & Angra, S. (2019a). Automatic guided vehicle systems in flexible manufacturing sys-tem–A review. International Journal of Industrial Engineering: Theory, Applications and Practice, 26(5).
Chawla, V. K., Chanda, A. K., Angra, S., & Rani, S. (2019b). Effect of nature-inspired algorithms and hybrid dispatch-ing rules on the performance of automatic guided vehicles in the flexible manufacturing system. Journal of the Bra-zilian Society of Mechanical Sciences and Engineering, 41, 1-17.
Chawla, V. K., Chhabra, D., Gupta, P., & Naaz, S. (2021). Evaluation of green operations management by fuzzy analyti-cal hierarchy process. Materials Today: Proceedings, 38, 274-279.
Chawla, V., Angra, S., Suri, S., & Kalra, R. (2020). A synergic framework for cyber-physical production systems in the context of industry 4.0 and beyond. International Journal of Data and Network Science, 4(2), 237-244.
Chawla, V., Chanda, A., & Angra, S. (2018). Sustainable multi-objective scheduling for automatic guided vehicle and flexible manufacturing system by a grey wolf optimization algorithm. International Journal of Data and Network Science, 2(1), 27-40.
Chawla, V., Chanda, A., & Angra, S. (2019c). Material handling robots fleet size optimization by a heuristic. Journal of Project Management, 4(3), 177-184.
de Paula Vidal, G. H., Caiado, R. G. G., Scavarda, L. F., Ivson, P., & Garza-Reyes, J. A. (2022). Decision support framework for inventory management combining fuzzy multicriteria methods, genetic algorithm, and artificial neu-ral network. Computers & Industrial Engineering, 174, 108777.
Diaby, V., Campbell, K., & Goeree, R. (2013). Multi-criteria decision analysis (MCDA) in health care: a bibliometric analysis. Operations Research for Health Care, 2(1-2), 20-24.
Dodgson, J. S., Spackman, M., Pearman, A., & Phillips, L. D. (2009). Multi-criteria analysis: a manual.
Dwivedi, P., Siddiquee, A. N., & Maheshwari, S. (2021). Issues and requirements for aluminum alloys used in aircraft components: state of the art. Russian Journal of Non-Ferrous Metals, 62, 212-225.
Fan, Z. P., Zhang, X., Chen, F. D., & Liu, Y. (2013). Extended TODIM method for hybrid multiple attribute decision making problems. Knowledge-Based Systems, 42, 40-48.
Ghorabaee, M. K., Zavadskas, E. K., Amiri, M., & Turskis, Z. (2016). Extended EDAS method for fuzzy multi-criteria decision-making: an application to supplier selection. International journal of computers communications & con-trol, 11(3), 358-371.
Gomes, L. F. A. M., & Lima, M. M. P. P. (1991). TODIMI: Basics and application to multicriteria ranking. Found. Comput. Decis. Sci, 16(3-4), 1-16.
Gomes, L. F. A. M., Rangel, L. A. D., & Maranhão, F. J. C. (2009). Multicriteria analysis of natural gas destination in Brazil: An application of the TODIM method. Mathematical and Computer Modelling, 50(1-2), 92-100.
Gupta, P., Chawla, V., Jain, V., & Angra, S. (2022). Green operations management for sustainable development: An ex-plicit analysis by using fuzzy best-worst method. Decision Science Letters, 11(3), 357-366.
Hadi-Vencheh, A., & Mohamadghasemi, A. (2011). A fuzzy AHP-DEA approach for multiple criteria ABC inventory classification. Expert Systems with Applications, 38(4), 3346-3352.
Hayashi, K. (2000). Multicriteria analysis for agricultural resource management: a critical survey and future perspec-tives. European journal of operational research, 122(2), 486-500.
Huang, J. J., Tzeng, G. H., & Liu, H. H. (2009). A revised VIKOR model for multiple criteria decisions making-The per-spective of regret theory. In Cutting-Edge Research Topics on Multiple Criteria Decision Making: 20th Internation-al Conference, MCDM 2009, Chengdu/Jiuzhaigou, China, June 21-26, 2009. Proceedings (pp. 761-768). Springer Berlin Heidelberg.
Huang, J., Li, Z. S., & Liu, H. C. (2017). New approach for failure mode and effect analysis using linguistic distribution assessments and TODIM method. Reliability Engineering & System Safety, 167, 302-309.
Kaabi, H., Jabeur, K., & Ladhari, T. (2018). A genetic algorithm-based classification approach for multicriteria ABC analysis. International Journal of Information Technology & Decision Making, 17(06), 1805-1837.
Kahraman, C., Keshavarz Ghorabaee, M., Zavadskas, E. K., Cevik Onar, S., Yazdani, M., & Oztaysi, B. (2017). Intui-tionistic fuzzy EDAS method: an application to solid waste disposal site selection. Journal of Environmental Engi-neering and Landscape Management, 25(1), 1-12.
Kaur, P., Pradhan, B. L., & Priya, A. (2022). TODIM approach for selection of inventory policy in supply chain. Mathematical Problems in Engineering, 2022.
Li, M., Wu, C., Zhang, L., & You, L. N. (2015). An intuitionistic fuzzy-TODIM method to solve distributor evaluation and selection problem. International Journal of Simulation Modelling, 14(3), 511-524.
Liang, D., Zhang, Y., Xu, Z., & Jamaldeen, A. (2019). Pythagorean fuzzy VIKOR approaches based on TODIM for eval-uating internet banking website quality of Ghanaian banking industry. Applied soft computing, 78, 583-594.
Mulliner, E., Malys, N., & Maliene, V. (2016). Comparative analysis of MCDM methods for the assessment of sustain-able housing affordability. Omega, 59, 146-156.
Naeini, A. B., Mojaradi, B., Zamani, M., & Chawla, V. K. (2019). Prevention of cardiovascular diseases by combining GIS with fuzzy best-worst decision-making algorithm in areas of Tehran. International Journal of Industrial Engi-neering and Production Research, 30(3), 255-271.
Opricovic, S. (2016). A comparative analysis of the DEA-CCR model and the VIKOR method. Yugoslav Journal of Op-erations Research, 18(2).
Opricovic, S., & Tzeng, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European journal of operational research, 156(2), 445-455.
Parashar, S., & Chawla, V. (2023). Kenaf-Coir based hybrid nano-composite: an analytical and representative volume element analysis. Engineering Solid Mechanics, 11(1), 103-118.
Parashar, S., & Chawla, V. K. (2021). A systematic review on sustainable green fibre reinforced composite and their an-alytical models. Materials Today: Proceedings, 46, 6541-6546.
Partovi, F. Y., & Anandarajan, M. (2002). Classifying inventory using an artificial neural network approach. Computers & Industrial Engineering, 41(4), 389-404.
Partovi, F. Y., & Burton, J. (1993). Using the analytic hierarchy process for ABC analysis. International Journal of Op-erations & Production Management.
Pol, A., Malagi, R., & Munshi, G. (2022). Identification of mechanical properties of an araldite LY556 blended with DNR composite and polyacetal: A comparative study for sustainable future. Journal of Future Sustainability, 2(4), 149-156.
Rabbani, A., Zamani, M., Yazdani-Chamzini, A., & Zavadskas, E. K. (2014). Proposing a new integrated model based on sustainability balanced scorecard (SBSC) and MCDM approaches by using linguistic variables for the perfor-mance evaluation of oil producing companies. Expert systems with applications, 41(16), 7316-7327.
Rahman, M. Z., Siddiquee, A. N., Khan, Z. A., & Ahmad, S. (2022). Multi-response optimization of FSP parameters on mechanical properties of surface composite. Materials Today: Proceedings, 62, 5-8.
Rauf, M., Guan, Z., Sarfraz, S., Mumtaz, J., Almaiman, S., Shehab, E., & Jahanzaib, M. (2018, September). Multi-criteria inventory classification based on multi-criteria decision-making (MCDM) technique. In Advances in Manu-facturing Technology XXXII: Proceedings of the 16th International Conference on Manufacturing Research, incor-porating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden (Vol. 8, p. 343). IOS Press.
Ren, L., Zhang, Y., Wang, Y., & Sun, Z. (2007). Comparative analysis of a novel M-TOPSIS method and TOP-SIS. Applied Mathematics Research eXpress, 2007.
Sadjadi, S. (2021). A survey on the effect of plastic pollution in the Great Lakes. Journal of Future Sustainability, 1(1), 5-8.
Sadjadi, S. S., & Ghaderi, S. F. (2023). The role of interest rate and inflation on oil stock prices: Evidence from Ukraine-Russia war. Journal of Industrial and Systems Engineering, 14(4), 174-181.
Sánchez-Lozano, J. M., Teruel-Solano, J., Soto-Elvira, P. L., & García-Cascales, M. S. (2013). Geographical Infor-mation Systems (GIS) and Multi-Criteria Decision Making (MCDM) methods for the evaluation of solar farms loca-tions: Case study in south-eastern Spain. Renewable and sustainable energy reviews, 24, 544-556.
Saxena, T., & Chawla, V. K. (2021). Banana leaf fiber-based green composite: An explicit review report. Materials To-day: Proceedings, 46, 6618-6624.
Saxena, T., & Chawla, V. K. (2022). Evaluation of mechanical properties for banana-carbon fiber reinforced nano-clay epoxy composite using analytical modeling and simulation. Research on Engineering Structures and Materials, 8(4), 773-798.
Shyur, H. J., & Shih, H. S. (2006). A hybrid MCDM model for strategic vendor selection. Mathematical and computer modelling, 44(7-8), 749-761.
Touni, Z., Makui, A., & Mohammadi, E. (2019). A MCDM-based approach using UTA-STRAR method to discover behavioral aspects in stock selection problem. International Journal of Industrial Engineering and Production Research, 30(1), 93-103.
Van den Berg, J. P., & Zijm, W. H. (1999). Models for warehouse management: Classification and exam-ples. International journal of production economics, 59(1-3), 519-528.
Wang, P., Zhu, Z., & Wang, Y. (2016). A novel hybrid MCDM model combining the SAW, TOPSIS and GRA methods based on experimental design. Information Sciences, 345, 27-45.
Wang, S., & Liu, J. (2017). Extension of the TODIM method to intuitionistic linguistic multiple attribute decision making. Symmetry, 9(6), 95.
Wu, Q., Lin, W., Zhou, L., Chen, Y., & Chen, H. (2019). Enhancing multiple attribute group decision making flexibility based on information fusion technique and hesitant Pythagorean fuzzy sets. Computers & Industrial Engineer-ing, 127, 954-970.
Yadav, E., & Chawla, V. K. (2022a). An explicit literature review on bearing materials and their defect detection tech-niques. Materials Today: Proceedings, 50, 1637-1643.
Yadav, E., & Chawla, V. K. (2022b). Fault detection in rotating elements by using fuzzy integrated improved local bina-ry pattern method. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 44(12), 596.
Yager, R. R., & Abbasov, A. M. (2013). Pythagorean membership grades, complex numbers, and decision mak-ing. International Journal of Intelligent Systems, 28(5), 436-452.
Zadeh, L. (1965). Fuzzy sets. Inform Control, 8, 338-353.
Zanakis, S. H., Solomon, A., Wishart, N., & Dublish, S. (1998). Multi-attribute decision making: A simulation compari-son of select methods. European journal of operational research, 107(3), 507-529.
Zavadskas, E. K., Mardani, A., Turskis, Z., Jusoh, A., & Nor, K. M. (2016). Development of TOPSIS method to solve complicated decision-making problems—An overview on developments from 2000 to 2015. International Journal of Information Technology & Decision Making, 15(03), 645-682.