COPRAS method for multiple attribute group decision making under picture fuzzy environment and their application to green supplier selection
Abstract
The green supplier selection (GSS) is a significant part in green supply chain management (GSCM). Choosing optimal green supplier can not only realize the sustainable development of enterprises, but also maximize the utilization rate of resources and diminish the negative effect of environmental issues, which conforms to the theme of green development. As a multiple attribute group decision-making (MAGDM) issue, selecting optimal green supplier is of vital important to enterprises. However, how to select the optimal supplier for enterprises is a great challenge. To handle this issue, a novel picture fuzzy COPRAS (COmplex PRoportional Assessment) method is devised. First, some necessary theories related to picture fuzzy sets (PFSs) are briefly reviewed. In addition, a method called CRITIC (Criteria Importance Though Intercrieria Correlation) is utilized to calculate criteria’s weights. Afterwards, the conventional COPRAS method is extended to the PFSs to calculate each alternative’s utility degree. At last, the designed method is exacted to an application which is related to GSS and there also conduct some comparative analysis to demonstrate the designed method’s superiority. The final results show that the proposed model can be utilized to decide the optimum green supplier.
Keyword : multiple attribute group decision-making (MAGDM), picture fuzzy sets (PFSs), COPRAS method, CRITIC method, green supplier selection
How to Cite
Lu, J., Zhang, S., Wu, J., & Wei, Y. (2021). COPRAS method for multiple attribute group decision making under picture fuzzy environment and their application to green supplier selection. Technological and Economic Development of Economy, 27(2), 369-385. https://doi.org/10.3846/tede.2021.14211
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Garg, H. (2017). Some picture fuzzy aggregation operators and their applications to multicriteria decision-making. Arabian Journal for Science and Engineering, 42, 5275–5290. https://doi.org/10.1007/s13369-017-2625-9
Harridan, S., & Cheaitou, A. (2017). Supplier selection and order allocation with green criteria: An MCDM and multi-objective optimization approach. Computers & Operations Research, 81, 282–304. https://doi.org/10.1016/j.cor.2016.11.005
He, T. T., Wei, G. W., Lu, J. P., Wei, C., & Lin, R. (2019). Pythagorean 2-tuple linguistic taxonomy method for supplier selection in medical instrument industries. International Journal of Environmental Research and Public Health, 16(23), 4875. https://doi.org/10.3390/ijerph16234875
Ho, W., Xu, X. W., & Dey, P. K. (2010). Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of Operational Research, 202, 16–24. https://doi.org/10.1016/j.ejor.2009.05.009
Jin, Y., Wu, H. C., Sun, D. C., Zeng, S. Z., Luo, D. D., & Peng, B. (2019). A multi-attribute pearson’s picture fuzzy correlation-based decision-making method. Mathematics, 7(10), 999. https://doi.org/10.3390/math7100999
Kaya, R., & Yet, B. (2019). Building Bayesian networks based on DEMATEL for multiple criteria decision problems: A supplier selection case study. Expert Systems with Applications, 134, 234–248. https://doi.org/10.1016/j.eswa.2019.05.053
Keshavarz Ghorabaee, M., Amiri, M., Sadaghiani, J. S., & Goodarzi, G. H. (2014). Multiple criteria group decision-making for supplier selection based on COPRAS method with interval type-2 fuzzy sets. International Journal of Advanced Manufacturing Technology, 75, 1115–1130. https://doi.org/10.1007/s00170-014-6142-7
Kilic, H. S., & Yalcin, A. S. (2020). Modified two-phase fuzzy goal programming integrated with IFTOPSIS for green supplier selection. Applied Soft Computing, 93, 106371. https://doi.org/10.1016/j.asoc.2020.106371
Li, Z. X., & Lu, M. (2019). Some novel similarity and distance measures of pythagorean fuzzy sets and their applications. Journal of Intelligent & Fuzzy Systems, 37, 1781–1799. https://doi.org/10.3233/JIFS-179241
Liang, W.-Z., Zhao, G.-Y., & Luo, S.-Z. (2018). An integrated EDAS-ELECTRE method with picture fuzzy information for cleaner production evaluation in gold mines. IEEE Access, 6, 65747–65759. https://doi.org/10.1109/ACCESS.2018.2878747
Liao, H. C., Long, Y. L., Ming, T., Mardani, A., & Xu, J. P. (2019). Low carbon supplier selection using a hesitant fuzzy linguistic span method integrating the analytic network process. Transformations in Business & Economics, 18, 67–87.
Lin, M. W., Huang, C., & Xu, Z. S. (2020). MULTIMOORA based MCDM model for site selection of car sharing station under picture fuzzy environment. Sustainable Cities and Society, 53, 101873. https://doi.org/10.1016/j.scs.2019.101873
Liu, K., Liu, Y., & Qin, J. (2018). An integrated ANP-VIKOR methodology for sustainable supplier selection with interval type-2 fuzzy sets. Granular Computing, 3, 193–208. https://doi.org/10.1007/s41066-017-0071-4
Lu, J. P., He, T. T., Wei, G. W., Wu, J., & Wei, C. (2020). Cumulative prospect theory: performance evaluation of government purchases of home-based elderly-care services using the pythagorean 2-tuple linguistic TODIM method. International Journal of Environmental Research and Public Health, 17(6), 1939. https://doi.org/10.3390/ijerph17061939
Lu, J. P., & Wei, C. (2019). TODIM method for performance appraisal on social-integration-based rural reconstruction with interval-valued intuitionistic fuzzy information. Journal of Intelligent & Fuzzy Systems, 37, 1731–1740. https://doi.org/10.3233/JIFS-179236
Makhesana, M. A. (2015). Application of improved complex proportional assessment (COPRAS) method for rapid prototyping system selection. Rapid Prototyping Journal, 21, 671–674. https://doi.org/10.1108/RPJ-03-2014-0027
Matić, B., Jovanović, S., Das, D. K., Zavadskas, E. K., & Marinković, M. (2019). A new hybrid MCDM model: sustainable supplier selection in a construction company. Symmetry, 11(3), 353. https://doi.org/10.3390/sym11030353
Min, H., & Kim, I. (2012). Green supply chain research: past, present, and future. Logistics Research, 4, 39–47. https://doi.org/10.1007/s12159-012-0071-3
Mohanty, R. P., & Prakash, A. (2014). Green supply chain management practices in India: an empirical study. Production Planning & Control, 25, 1322–1337. https://doi.org/10.1080/09537287.2013.832822
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