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Volume 8 Issue 9
Sep.  2021

IEEE/CAA Journal of Automatica Sinica

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Peide Liu and Hui Gao, "A Novel Green Supplier Selection Method Based on the Interval Type-2 Fuzzy Prioritized Choquet Bonferroni Means," IEEE/CAA J. Autom. Sinica, vol. 8, no. 9, pp. 1549-1566, Sept. 2021. doi: 10.1109/JAS.2020.1003444
Citation: Peide Liu and Hui Gao, "A Novel Green Supplier Selection Method Based on the Interval Type-2 Fuzzy Prioritized Choquet Bonferroni Means," IEEE/CAA J. Autom. Sinica, vol. 8, no. 9, pp. 1549-1566, Sept. 2021. doi: 10.1109/JAS.2020.1003444

A Novel Green Supplier Selection Method Based on the Interval Type-2 Fuzzy Prioritized Choquet Bonferroni Means

doi: 10.1109/JAS.2020.1003444
Funds:  This work was supported by the National Natural Science Foundation of China (71771140), Project of Cultural Masters and “the Four Kinds of a Batch” Talents, the Special Funds of Taishan Scholars Project of Shandong Province (ts201511045), and the Major Bidding Projects of National Social Science Fund of China (19ZDA080)
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  • In view of the environment competencies, selecting the optimal green supplier is one of the crucial issues for enterprises, and multi-criteria decision-making (MCDM) methodologies can more easily solve this green supplier selection (GSS) problem. In addition, prioritized aggregation (PA) operator can focus on the prioritization relationship over the criteria, Choquet integral (CI) operator can fully take account of the importance of criteria and the interactions among them, and Bonferroni mean (BM) operator can capture the interrelationships of criteria. However, most existing researches cannot simultaneously consider the interactions, interrelationships and prioritizations over the criteria, which are involved in the GSS process. Moreover, the interval type-2 fuzzy set (IT2FS) is a more effective tool to represent the fuzziness. Therefore, based on the advantages of PA, CI, BM and IT2FS, in this paper, the interval type-2 fuzzy prioritized Choquet normalized weighted BM operators with ${{ \lambda}}$ fuzzy measure and generalized prioritized measure are proposed, and some properties are discussed. Then, a novel MCDM approach for GSS based upon the presented operators is developed, and detailed decision steps are given. Finally, the applicability and practicability of the proposed methodology are demonstrated by its application in the shared-bike GSS and by comparisons with other methods. The advantages of the proposed method are that it can consider interactions, interrelationships and prioritizations over the criteria simultaneously.

     

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  • [1]
    I. Dobos and G. Vorosmarty, “Inventory-related costs in green supplier selection problems with data envelopment analysis (DEA),” Int. J. Prod. Econ., vol. 209, pp. 374–380, Mar. 2019. doi: 10.1016/j.ijpe.2018.03.022
    [2]
    Z. P. Tian, H. Y. Zhang, J. Q. Wang, and T. L. Wang, “Green supplier selection using improved TOPSIS and best-worst method under intuitionistic fuzzy environment,” Informatica, vol. 29, no. 4, pp. 773–800, Jan. 2018. doi: 10.15388/Informatica.2018.192
    [3]
    A. Awasthi and G. Kannan, “Green supplier development program selection using NGT and VIKOR under fuzzy environment,” Comput. Ind. Eng., vol. 91, pp. 100–108, Jan. 2016. doi: 10.1016/j.cie.2015.11.011
    [4]
    N. Banaeian, H. Mobli, B. Fahimnia, I. E. Nielsen, and M. Omid, “Green supplier selection using fuzzy group decision making methods: A case study from the agri-food industry,” Comput. Oper. Res., vol. 89, pp. 337–347, Jan. 2018. doi: 10.1016/j.cor.2016.02.015
    [5]
    L. Demir, M. E. Akpinar, C. Arza, and M. A. Ilgiotan, “A green supplier evaluation system based on a new multi-criteria sorting method: VIKORSORT,” Expert Syst. Appl., vol. 114, pp. 479–487, Dec. 2018. doi: 10.1016/j.eswa.2018.07.071
    [6]
    C. X. Yu, Y. F. Shao, K. Wang, and L. P. Zhang, “A group decision making sustainable supplier selection approach using extended TOPSIS under interval-valued Pythagorean fuzzy environment,” Expert Syst. Appl., vol. 121, pp. 1–17, May 2019. doi: 10.1016/j.eswa.2018.12.010
    [7]
    W. J. Cheng, A. Appolloni, A. DAmato, and Q. H. Zhu, “Green Public Procurement, missing concepts and future trends—A critical review,” J. Clean. Prod., vol. 176, pp. 770–784, Mar. 2018. doi: 10.1016/j.jclepro.2017.12.027
    [8]
    L. A. Zadeh, “The concept of a linguistic variable and its application to approximate reasoning—I,” Inform. Sci., vol. 8, no. 3, pp. 199–249, Jan. 1975. doi: 10.1016/0020-0255(75)90036-5
    [9]
    S. M. Chen and L. W. Kuo, “Autocratic decision making using group recommendations based on interval type-2 fuzzy sets, enhanced Karnik-Mendel algorithms, and the ordered weighted aggregation operator,” Inform. Sci., vol. 412-413, pp. 174–193, Oct. 2017. doi: 10.1016/j.ins.2017.05.030
    [10]
    C. M. T. Yip, W. W. Tan, and M. W. Nie, “On the difference in control performance of interval type-2 fuzzy PI control system with different FOU shapes,” Appl. Soft Comput., vol. 76, pp. 517–532, Mar. 2019. doi: 10.1016/j.asoc.2018.12.039
    [11]
    R. M. Li, Y. F. Huang, and J. Wang, “Long-term traffic volume prediction based on K-means Gaussian interval type-2 fuzzy sets,” IEEE/CAA J. Autom. Sinica, vol. 6, no. 6, pp. 1344–1351, Nov. 2019.
    [12]
    Q. Wu, L. G. Zhou, Y. Chen, and H. Y. Chen, “An integrated approach to green supplier selection based on the interval type-2 fuzzy best-worst and extended VIKOR methods,” Inform. Sci., vol. 502, pp. 394–417, Oct. 2019. doi: 10.1016/j.ins.2019.06.049
    [13]
    J. D. Qin, X. W. Liu, and W. Pedrycz, “An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment,” Eur. J. Oper. Res., vol. 258, no. 2, pp. 626–638, Apr. 2017. doi: 10.1016/j.ejor.2016.09.059
    [14]
    S. Mousakhani, S. Nazari-Shirkouhi, and A. Bozorgi-Amiri, “A novel interval type-2 fuzzy evaluation model based group decision analysis for green supplier selection problems: A case study of battery industry,” J. Clean. Prod., vol. 168, pp. 205–218, Dec. 2017. doi: 10.1016/j.jclepro.2017.08.154
    [15]
    M. K. Ghorabaee, E. K. Zavadskas, M. Amiri, and A. Esmaeili, “Multi-criteria evaluation of green suppliers using an extended WASPAS method with interval type-2 fuzzy sets,” J. Clean. Prod., vol. 137, pp. 213–229, Nov. 2016. doi: 10.1016/j.jclepro.2016.07.031
    [16]
    Z. M. Zhang, “Trapezoidal interval type-2 fuzzy aggregation operators and their application to multiple attribute group decision making,” Neural Comput. Appl., vol. 29, pp. 1039–1054, Feb. 2018. doi: 10.1007/s00521-016-2488-0
    [17]
    M. Grabisch, T. Murofushi, and M. Sugeno, Fuzzy Measures and Integrals: Theory and Applications. Heidelberg, Germany: Physica-Verlag, 2000, pp. 314–319.
    [18]
    A. Mesiarova-Zemankova, S. Kelly, and K. Ahmad, “Bonferroni mean with weighted interaction,” IEEE Trans. Fuzzy Syst., vol. 26, no. 5, pp. 3085–3096, Oct. 2018. doi: 10.1109/TFUZZ.2018.2792475
    [19]
    C. Bonferroni, “Sulle medie multiple di potenze,” Bollettino DellUnione Matematica Italiana, vol. 5, no. 3–4, pp. 267–270, 1950.
    [20]
    J. X. Xie and Y. Xue, The Basic Method of Using LINGO Software in Optimization Model and LINDO/LINGO Software. Beijing, China: Tsinghua University Press, 2005, pp. 79–116.
    [21]
    R. R. Yager, C. L. Walker, and E. A. Walker, “A prioritized measure for multi-criteria aggregation and its Shapley index,” in Proc. Annu. Meeting of the North American Fuzzy Information Processing Society, El Paso, TX, USA, 2011, pp. 1–4.
    [22]
    Y. N. Wu, C. B. Xu, Y. Huang, and X. Y. Li, “Green supplier selection of electric vehicle charging based on Choquet integral and type-2 fuzzy uncertainty,” Soft Comput., vol. 24, pp. 3781–3795, Mar. 2020. doi: 10.1007/s00500-019-04147-4
    [23]
    J. Q. Liu, J. J. Xue, L. Yang, and B. S. Shi, “Enhancing green public procurement practices in local governments: Chinese evidence based on a new research framework,” J. Clean. Prod., vol. 211, pp. 842–854, Feb. 2019. doi: 10.1016/j.jclepro.2018.11.151
    [24]
    B. D. Rouyendegh, A. Yildizbasi, and P. Ustunyer, “Intuitionistic Fuzzy TOPSIS method for green supplier selection problem,” Soft Comput., vol. 24, pp. 2215–2228, Feb. 2020. doi: 10.1007/s00500-019-04054-8
    [25]
    K. Govindan, S. Rajendran, J. Sarkis, and P. Murugesan, “Multi criteria decision making approaches for green supplier evaluation and selection: A literature review,” J. Clean. Prod., vol. 98, pp. 66–83, Jul. 2015. doi: 10.1016/j.jclepro.2013.06.046
    [26]
    S. Hamdan and A. Cheaitou, “Dynamic green supplier selection and order allocation with quantity discounts and varying supplier availability,” Comput. Ind. Eng., vol. 110, pp. 573–589, Aug. 2017. doi: 10.1016/j.cie.2017.03.028
    [27]
    P. D. Liu, H. Gao, and J. H. Ma, “Novel green supplier selection method by combining quality function deployment with partitioned Bonferroni mean operator in interval type-2 fuzzy environment,” Inform. Sci., vol. 490, pp. 292–316, Jul. 2019. doi: 10.1016/j.ins.2019.03.079
    [28]
    P. Ghadimi, F. G. Toosi, and C. Heavey, “A multi-agent systems approach for sustainable supplier selection and order allocation in a partnership supply chain,” Eur. J. Oper. Res., vol. 269, no. 1, pp. 286–301, Aug. 2018. doi: 10.1016/j.ejor.2017.07.014
    [29]
    J. J. Peng, C. Tian, W. Y. Zhang, S. Zhang, and J. Q. Wang, “An integrated multi-criteria decision-making framework for sustainable supplier selection under picture fuzzy environment,” Technol. Econ. Dev. Eco., vol. 26, no. 3, pp. 573–598, Jun. 2020. doi: 10.3846/tede.2020.12110
    [30]
    K. Govindan, M. Kadzinski, and R. Sivakumar, “Application of a novel PROMETHEE-based method for construction of a group compromise ranking to prioritization of green suppliers in food supply chain,” Omega, vol. 71, pp. 129–145, Sep. 2017. doi: 10.1016/j.omega.2016.10.004
    [31]
    S. A. S. Haeri and J. Rezaei, “A grey-based green supplier selection model for uncertain environments,” J. Clean. Prod., vol. 221, pp. 768–784, Jun. 2019. doi: 10.1016/j.jclepro.2019.02.193
    [32]
    F. F. Jin, Z. W. Ni, and H. Y. Chen, “Note on “Hesitant fuzzy prioritized operators and their application to multiple attribute decision making”,” Knowl.-Based Syst., vol. 96, pp. 115–119, Mar. 2016. doi: 10.1016/j.knosys.2015.12.023
    [33]
    H. M. Nehi and A. Keikha, “TOPSIS and Choquet integral hybrid technique for solving MAGDM problems with interval type-2 fuzzy numbers,” J. Intell. Fuzzy Syst., vol. 30, no. 3, pp. 1301–1310, Mar. 2016. doi: 10.3233/IFS-152044
    [34]
    Y. B. Gong, N. Hu, J. G. Zhang, G. F. Liu, and J. G. Deng, “Multi-attribute group decision making method based on geometric Bonferroni mean operator of trapezoidal interval type-2 fuzzy numbers,” Comput. Ind. Eng., vol. 81, pp. 167–176, Mar. 2015. doi: 10.1016/j.cie.2014.12.030
    [35]
    L. Wang, H. Y. Zhang, and J. Q. Wang, “Frank Choquet Bonferroni mean operators of Bipolar Neutrosophic sets and their application to multi-criteria decision-Making problems,” Int. J. Fuzzy Syst., vol. 20, no. 1, pp. 13–28, Jan. 2018. doi: 10.1007/s40815-017-0373-3
    [36]
    W. Zhou and J. M. He, “Intuitionistic fuzzy normalized weighted Bonferroni mean and its application in multicriteria decision making,” J. Appl. Math., vol. 2012, Article No. 136254, Sep. 2012.
    [37]
    R. X. Nie, Z. P. Tian, J. Q. Wang, and J. H. Hu, “Pythagorean fuzzy multiple criteria decision analysis based on Shapley fuzzy measures and partitioned normalized weighted Bonferroni mean operator,” Int. J. Intell. Syst., vol. 34, no. 2, pp. 297–324, Feb. 2019. doi: 10.1002/int.22051
    [38]
    L. H. Yang and B. L. Li, “An extended single-valued neutrosophic normalized weighted Bonferroni mean Einstein aggregation operator,” Int. J. Appl. Math., vol. 48, no. 4, pp. 1–8, Nov. 2018.
    [39]
    X. H. Yu and Z. S. Xu, “Prioritized intuitionistic fuzzy aggregation operators,” Inform. Fusion, vol. 14, no. 1, pp. 108–116, Jan. 2013. doi: 10.1016/j.inffus.2012.01.011
    [40]
    P. D. Liu, Q. Khan, and T. Mahmood, “Multiple-attribute decision making based on single-valued neutrosophic Schweizer-Sklar prioritized aggregation operator,” Cogn. Syst. Res., vol. 57, pp. 175–196, Oct. 2019. doi: 10.1016/j.cogsys.2018.10.005
    [41]
    J. M. Mendel, “Type-2 fuzzy sets and systems: An overview,” IEEE Comput. Intell. Mag., vol. 2, no. 1, pp. 20–29, Feb. 2007. doi: 10.1109/MCI.2007.380672
    [42]
    G. E. Martinez, D. O. Mendoza, J. R. Castro, P. Melin, and O. Castillo, “Choquet integral and interval type-2 fuzzy Choquet integral for edge detection,” in Nature-Inspired Design of Hybrid Intelligent Systems, P. Melin, O. Castillo, and J. Kacprzyk, Eds. Springer, 2017, pp. 79–97.
    [43]
    Q. L. Liang and J. M. Mendel, “Interval type-2 fuzzy logic systems: Theory and design,” IEEE Trans. Fuzzy Syst., vol. 8, no. 5, pp. 535–550, Oct. 2000. doi: 10.1109/91.873577
    [44]
    T. Murofushi and M. Sugeno, “An interpretation of fuzzy measures and the Choquet integral as an integral with respect to a fuzzy measure,” Fuzzy Set. Syst., vol. 29, no. 2, pp. 201–227, Jan. 1989. doi: 10.1016/0165-0114(89)90194-2
    [45]
    P. D. Liu and G. L. Tang, “Some intuitionistic fuzzy prioritized interactive Einstein Choquet operators and their application in decision making,” IEEE Access, vol. 6, pp. 72357–72371, Nov. 2018. doi: 10.1109/ACCESS.2018.2882071
    [46]
    L. H. Chen, Z. S. Xu, and X. H. Yu, “Prioritized measure-guided aggregation operators,” IEEE Trans. Fuzzy Syst., vol. 22, no. 5, pp. 1127–1138, Oct. 2014. doi: 10.1109/TFUZZ.2013.2282169
    [47]
    P. D. Liu, S. M. Chen, and J. L. Liu, “Multiple attribute group decision making based on intuitionistic fuzzy interaction partitioned Bonferroni mean operators,” Inform. Sci., vol. 411, pp. 98–121, Oct. 2017. doi: 10.1016/j.ins.2017.05.016
    [48]
    R. Wang, B. Shuai, Z. S. Chen, K. S. Chin, and J. H. Zhu, “Revisiting the role of hesitant multiplicative preference relations in group decision making with novel consistency improving and consensus reaching processes,” Int. J. Comput. Intell. Syst., vol. 12, no. 2, pp. 1029–1046, Sep. 2019. doi: 10.2991/ijcis.d.190823.001

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    Highlights

    • The IT2FSs are applied to express the uncertainties of the GSS since they have obvious advantage of dealing with high order uncertainties more precisely;
    • IT2FPCNWBM with λ fuzzy measure and GPM by combining PA operator, CI operator and BM operator are proposed respectively, so as to consider interactions, interrelationships and prioritizations over the criteria simultaneously;
    • A novel GSS method based on the presented aggregation operators is developed;
    • A case of shared-bike GSS is conducted to validate the applicability and practicability of the proposed method, and a richer comparative analysis is utilized to explain the superiority and feasibility of the novel method.

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