EDAS method for multiple criteria group decision making with picture fuzzy information and its application to green suppliers selections
Abstract
In this paper, we construct picture fuzzy EDAS model based on traditional EDAS (Evaluation based on Distance from Average Solution) model. Firstly, we briefly review the definition of picture fuzzy sets (PFSs) and introduce the score function, accuracy function and operational laws of picture fuzzy numbers (PFNs). Then, we combine traditional EDAS model for MCGDM with PFNs. In our model, it’s more accuracy and effective for considering the conflicting attributes. Finally, a numerical example for green supplier selection has been given to illustrate this new model and some comparisons between EDAS model with PFNs and PFWA, PFWG aggregation operators are also conducted to further illustrate advantages of the new method.
First published online 23 August 2019
Keyword : multiple criteria group decision making (MCGDM) problems, picture fuzzy sets (PFSs), EDAS model, picture fuzzy weighted average (PFWA) operator, picture fuzzy weighted geometric (PFWG) operator, picture fuzzy EDAS model, green supplier selection
How to Cite
Zhang, S., Wei, G., Gao, H., Wei, C., & Wei, Y. (2019). EDAS method for multiple criteria group decision making with picture fuzzy information and its application to green suppliers selections. Technological and Economic Development of Economy, 25(6), 1123-1138. https://doi.org/10.3846/tede.2019.10714
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Aydin, S. (2018). Augmented reality goggles selection by using neutrosophic MULTIMOORA method. Journal of Enterprise Information Management, 31, 565-576. https://doi.org/10.1108/JEIM-01-2018-0023
Chen, N., & Xu, Z. S. (2015). Hesitant fuzzy ELECTRE II approach: A new way to handle multi-criteria decision making problems. Information Sciences, 292, 175-197. https://doi.org/10.1016/j.ins.2014.08.054
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Cuong, B. C., & Kreinovich, V. (2013). Picture Fuzzy Sets – a new concept for computational intelligence problems. IEEE. https://doi.org/10.1109/WICT.2013.7113099
Deng, X. M., Wei, G. W., Gao, H., & Wang, J. (2018). Models for Safety Assessment of Construction Project With Some 2-Tuple Linguistic Pythagorean Fuzzy Bonferroni Mean Operators. IEEE Access, 6, 52105-52137. https://doi.org/10.1109/ACCESS.2018.2869414
Ecer, F. (2018). Third-party logistics (3PLS) provider selection via fuzzy ahp and EDAS integrated model. Technological and Economic Development of Economy, 24, 615-634. https://doi.org/10.3846/20294913.2016.1213207
Feng, X. Q., Wei, C. P., & Liu, Q. (2018). EDAS method for extended hesitant fuzzy linguistic multicriteria decision making. International Journal of Fuzzy Systems, 20, 2470-2483. https://doi.org/10.1007/s40815-018-0504-5
Gao, H. (2018). Pythagorean fuzzy Hamacher Prioritized aggregation operators in multiple attribute decision making. Journal of Intelligent & Fuzzy Systems, 35, 2229-2245. https://doi.org/10.3233/JIFS-172262
Gao, H., Lu, M., Wei, G. W., & Wei, Y. (2018). Some novel pythagorean fuzzy interaction aggregation operators in multiple attribute decision making. Fundamenta Informaticae, 159, 385-428. https://doi.org/10.3233/FI-2018-1669
Hajlaoui, S., & Halouani, N. (2013). Hesitant-Fuzzy-Promethee method. In 2013 5th International Conference on Modeling, Simulation and Applied Optimization. https://doi.org/10.1109/ICMSAO.2013.6552710
Huang, Y. H., & Wei, G. W. (2018). TODIM method for Pythagorean 2-tuple linguistic multiple attribute decision making. Journal of Intelligent & Fuzzy Systems, 35, 901-915. https://doi.org/10.3233/JIFS-171636
Hung, W. L., & Yang, M. S. (2004). Similarity measures of intuitionistic fuzzy sets based on Hausdorff distance. Pattern Recognition Letters, 25, 1603-1611. https://doi.org/10.1016/j.patrec.2004.06.006
Ilieva, G. (2018). Group Decision Analysis Algorithms with EDAS for Interval Fuzzy Sets. Cybernetics and Information Technologies, 18, 51-64. https://doi.org/10.2478/cait-2018-0027
Ji, P., Zhang, H. Y., & Wang, J. Q. (2018). A projection-based TODIM method under multi-valued neutrosophic environments and its application in personnel selection. Neural Computing & Applications, 29, 221-234. https://doi.org/10.1007/s00521-016-2436-z
Kahraman, C., Keshavarz Ghorabaee, M., Zavadskas, E. K., Onar, S. C., Yazdani, M., & Oztaysi, B. (2017). Intuitionistic fuzzy EDAS method: An application to solid waste disposal site selection. Journal of Environmental Engineering and Landscape Management, 25, 1-12. https://doi.org/10.3846/16486897.2017.1281139
Karasan, A., & Kahraman, C. (2018a). Interval-Valued Neutrosophic Extension of EDAS Method. In J. Kacprzyk, E. Szmidt, S. Zadrozny, K. T. Atanassov & M. Krawczak (Eds.), Advances in Fuzzy Logic and Technology 2017, (Vol. 642, pp. 343-357). https://doi.org/10.1007/978-3-319-66824-6_31
Karasan, A., & Kahraman, C. (2018b). A novel interval-valued neutrosophic EDAS method: prioritization of the United Nations national sustainable development goals. Soft Computing, 22, 4891-4906. https://doi.org/10.1007/s00500-018-3088-y
Keshavarz-Ghorabaee, M., Amiri, M., Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2018a). A comparative analysis of the rank reversal phenomenon in the EDAS and TOPSIS methods. Economic Computation and Economic Cybernetics Studies and Research, 52, 121-134. https://doi.org/10.24818/18423264/52.3.18.08
Keshavarz-Ghorabaee, M., Amiri, M., Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2018b). A Dynamic Fuzzy Approach Based on the EDAS Method for multi-criteria subcontractor evaluation. Information, 9, 68. https://doi.org/10.3390/info9030068
Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., & Turskis, Z. (2017). Multi-criteria group decision-making using an extended edas method with interval type-2 fuzzy sets. E & M Ekonomie a Management, 20, 48-68. https://doi.org/10.15240/tul/001/2017-1-004
Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2017a). A new multi-criteria model based on interval type-2 fuzzy sets and EDAS method for supplier evaluation and order allocation with environmental considerations. Computers & Industrial Engineering, 112, 156-174. https://doi.org/10.1016/j.cie.2017.08.017
Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2017b). Stochastic EDAS method for multi-criteria decision-making with normally distributed data. Journal of Intelligent & Fuzzy Systems, 33, 1627-1638. https://doi.org/10.3233/JIFS-17184
Keshavarz Ghorabaee, M., 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 & Control, 11, 358-371. https://doi.org/10.15837/ijccc.2016.3.2557
Keshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., & Turskis, Z. (2015). Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica, 26, 435-451. https://doi.org/10.15388/Informatica.2015.57
Li, D. F. (2004). Some measures of dissimilarity in intuitionistic fuzzy structures. Journal of Computer and System Sciences, 68, 115-122. https://doi.org/10.1016/j.jcss.2003.07.006
Li, Z. X., Wei, G. W., & Lu, M. (2018). Pythagorean fuzzy hamy mean operators in multiple attribute group decision making and their application to supplier selection. Symmetry-Basel, 10. https://doi.org/10.3390/sym10100505
Liao, H. C., Si, G. S., Xu, Z. S., & Fujita, H. (2018). Hesitant fuzzy linguistic preference utility set and its application in selection of fire rescue plans. International Journal of Environmental Research and Public Health, 15. https://doi.org/10.3390/ijerph15040664
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