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Sustainable supplier selection by a new possibilistic hierarchical model in the context of Z-information

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Abstract

In recent years, supplier selection has been significantly important with respect to dimensions and criteria of sustainability. Organizations need to try to choose their suppliers based on how well their performances are in each of the economic, social, and environmental criteria. On the other hand, since the methods of supplier selection depend on the experts’ opinions, which have the potential of uncertainty and ambiguity, using Fuzzy sets to evaluate the criteria can be useful. Apart from considering experts’ opinions on a fuzzy basis, probabilities are considered in experts’ opinions via Z-numbers in order to increase the reliability of the data and the results. In this paper, after reviewing the literature, identifying the sustainability criteria, and step-by-step explaining the presented method, a numerical example is studied for more clarification. Moreover, the results of the conventional fuzzy sets are obtained and have been compared with those considering the probabilities (Z-number) leading to the conclusion that applying the experts’ opinions will be effective in ranking the suppliers.

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References

  • Aboutorab H, Saberi M, Asadabadi MR, Hussain O, Chang E (2018) ZBWM: the Z-number extension of best worst method and its application for supplier development. Expert Syst Appl 107:115–125

    Google Scholar 

  • Adamo J (1980) Fuzzy decision trees. Fuzzy Sets Syst 4:207–219

    MathSciNet  MATH  Google Scholar 

  • Amindoust A, Ahmed S, Saghafinia A, Bahreininejad A (2012) Sustainable supplier selection: a ranking model based on fuzzy inference system. Appl Soft Comput 12:1668–1677

    Google Scholar 

  • Awasthi A, Govindan K, Gold S (2018) Multi-tier sustainable global supplier selection using a fuzzy AHP-VIKOR based approach. Int J Prod Econ 195:106–117

    Google Scholar 

  • Banaeian N, Mobli H, Fahimnia B, Nielsen IE, Omid M (2018) Green supplier selection using fuzzy group decision making methods: a case study from the agri-food industry. Comput Oper Res 89:337–347

    MathSciNet  MATH  Google Scholar 

  • Burton TT (1988) JIT/repetitive sourcing strategies: ‘tying the knot’with Y. Prod Invent Manag J 29:38

    Google Scholar 

  • Büyüközkan G, Çifçi G (2011) A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information. Comput Ind 62:164–174

    Google Scholar 

  • Carlsson C, Fullér R (2009) Possibilistic mean value and variance of fuzzy numbers: some examples of application. In: 2009 IEEE International Conference on Fuzzy Systems, IEEE, pp 587–592

  • Chang B, Chang C-W, Wu C-H (2011) Fuzzy DEMATEL method for developing supplier selection criteria. Expert Syst Appl 38:1850–1858

    Google Scholar 

  • Chen S-M (1994) Fuzzy system reliability analysis using fuzzy number arithmetic operations. Fuzzy Sets Syst 64:31–38

    MathSciNet  Google Scholar 

  • Chen L, Yu H (2019) Emergency alternative selection based on an E-IFWA approach IEEE. Access 7:44431–44440

    Google Scholar 

  • Chen C-T, Lin C-T, Huang S-F (2006) A fuzzy approach for supplier evaluation and selection in supply chain management. Int J Prod Econ 102:289–301

    Google Scholar 

  • Dursun M, Karsak EE (2013) A QFD-based fuzzy MCDM approach for supplier selection. Appl Math Model 37:5864–5875

    MathSciNet  MATH  Google Scholar 

  • Erdoğan Z, Namlı E (2019) A living environment prediction model using ensemble machine learning techniques based on quality of life index. J Ambient Human Comput. https://doi.org/10.1007/s12652-019-01432-w

    Article  Google Scholar 

  • Fallahpour A, Olugu EU, Musa SN, Wong KY, Noori S (2017) A decision support model for sustainable supplier selection in sustainable supply chain management. Comput Ind Eng 105:391–410

    Google Scholar 

  • Fei L, Wang H, Chen L, Deng Y (2019) A new vector valued similarity measure for intuitionistic fuzzy sets based on OWA operators. Iran J Fuzzy Syst 16:113–126

    MathSciNet  MATH  Google Scholar 

  • Galankashi MR, Chegeni A, Soleimanynanadegany A, Memari A, Anjomshoae A, Helmi SA, Dargi A (2015) Prioritizing green supplier selection criteria using fuzzy analytical network process. Procedia CIRP 26:689–694

    Google Scholar 

  • Gören HG (2018) A decision framework for sustainable supplier selection and order allocation with lost sales. J Clean Prod 183:1156–1169

    Google Scholar 

  • Haider SW, Zhuang G, Ali S (2019) Identifying and bridging the attitude-behavior gap in sustainable transportation adoption Journal of Ambient Intelligence and Humanized. Computing 10:3723–3738

    Google Scholar 

  • Han Y, Deng Y, Cao Z, Lin C-T (2019) An interval-valued Pythagorean prioritized operator-based game theoretical framework with its applications in multicriteria group decision making. Neural Comput and Appl. https://doi.org/10.1007/s00521-019-04014-1

    Article  Google Scholar 

  • Hendiani S, Bagherpour M (2019a) Developing an integrated index to assess social sustainability in construction industry using fuzzy logic. J of Clean Prod 230:647–662

    Google Scholar 

  • Hendiani S, Bagherpour M (2019b) Development of sustainability index using Z-numbers: a new possibilistic hierarchical model in the context of Z-information. Environ Dev Sustain. https://doi.org/10.1007/s10668-019-00464-8

    Article  Google Scholar 

  • Ho W, Xu X, Dey PK (2010) Multi-criteria decision making approaches for supplier evaluation and selection: a literature review. Eur J Oper Res 202:16–24

    MATH  Google Scholar 

  • Humphreys P, Wong Y, Chan F (2003) Integrating environmental criteria into the supplier selection process. J Mater Process Technol 138:349–356

    Google Scholar 

  • Jirofti A, Najafi AA (2018) Portfolio selection using Z-number theory: two solution methodologies. Int J Fuzzy Syst 20:2484–2496

    MathSciNet  Google Scholar 

  • Joshi R (2019) A new multi-criteria decision-making method based on intuitionistic fuzzy information and its application to fault detection in a machine. J Ambient Intell Human Comput 11:739–753

    Google Scholar 

  • Kahraman C (2003) Multi-criteria supplier selection using fuzzy AHP. Log Inform Manag 16:382–394. https://doi.org/10.1108/09576050310503367

    Article  Google Scholar 

  • Kang B, Wei D, Li Y, Deng Y (2012) A method of converting Z-number to classical fuzzy number. J Inform Comput Sci 9:703–709

    Google Scholar 

  • Kang B, Zhang P, Gao Z, Chhipi-Shrestha G, Hewage K, Sadiq R (2019) Environmental assessment under uncertainty using Dempster-Shafer theory and Z-numbers. J Ambient Intell Human Comput. https://doi.org/10.1007/s12652-019-01228-y

    Article  Google Scholar 

  • Klir GJ, Yuan B (1995) Fuzzy sets and fuzzy logic: theory and applications. Prentice-Hall, Inc., United States

    MATH  Google Scholar 

  • Lascelles DM, Dale BG (1989) The buyer-supplier relationship in total quality management. J Purch Mater Manag 25:10–19

    Google Scholar 

  • Lee AH, Kang H-Y, Hsu C-F, Hung H-C (2009) A green supplier selection model for high-tech industry. Expert Syst Appl 36:7917–7927

    Google Scholar 

  • Lin C-T, Chiu H, Tseng Y-H (2006) Agility evaluation using fuzzy logic. Int J Prod Econ 101:353–368

    Google Scholar 

  • Mahler K (1968) An unsolved problem on the powers of 3/2. J Aust Math Soc 8:313–321

    MathSciNet  MATH  Google Scholar 

  • Marhamati N, Buxton EK, Rahimi S (2018) Integration of Z-numbers and Bayesian decision theory: a hybrid approach to decision making under uncertainty and imprecision. Appl Soft Comput 72:273–290

    Google Scholar 

  • Mehregan MR, Hashemi SH, Karimi A, Merikhi B (2014) Analysis of interactions among sustainability supplier selection criteria using ISM and fuzzy DEMATEL. Int J Appl Decis Sci 7:270–294

    Google Scholar 

  • Østergaard J-J (1976) Fuzzy logic control of a heat exchanger process. Stærkstrømsafdelingen, Danmarks Tekniske Højskole

    Google Scholar 

  • Öztürk BA, Özçelik F (2014) Sustainable supplier selection with a fuzzy multi-criteria decision making method based on triple bottom line. Bus Econ Res J 5:129

    Google Scholar 

  • Qiao D, Shen K-w, Wang J-q, Wang T-l (2019) Multi-criteria PROMETHEE method based on possibility degree with Z-numbers under uncertain linguistic environment. J Ambient Intell Human Comput. https://doi.org/10.1007/s12652-019-01251-z

    Article  Google Scholar 

  • Rashidi K, Cullinane K (2019) A comparison of fuzzy DEA and fuzzy TOPSIS in sustainable supplier selection: implications for sourcing strategy. Expert Syst Appl 121:266–281

    Google Scholar 

  • Sarwar A, Zeng Z, AduAgyapong R, ThiHoaiThuong N, Qadeer T (2017) A fuzzy multi-criteria decision making approach for supplier selection under fuzzy environment. In: Xu J, Gen M, Hajiyev A, Cooke F (eds) Proceedings of the eleventh international conference on management science and engineering management. ICMSEM 2017. Lecture notes on multidisciplinary industrial engineering. Springer, Cham

  • Shemshadi A, Shirazi H, Toreihi M, Tarokh MJ (2011) A fuzzy VIKOR method for supplier selection based on entropy measure for objective weighting. Expert Syst Appl 38:12160–12167

    Google Scholar 

  • Shen K-w, Wang J-q (2018) Z-VIKOR method based on a new comprehensive weighted distance measure of Z-number and its application. IEEE Trans Fuzzy Syst 26:3232–3245

    Google Scholar 

  • Wang Chen HM, Chou S-Y, Luu QD, Yu TH-K (2016) A fuzzy MCDM approach for green supplier selection from the economic and environmental aspects. Math Prob Eng. https://doi.org/10.1155/2016/8097386

    Article  Google Scholar 

  • Wang Y-M, Yang J-B, Xu D-L, Chin K-S (2006) On the centroids of fuzzy numbers. Fuzzy Sets Syst 157:919–926

    MathSciNet  MATH  Google Scholar 

  • Xiao F (2018) A hybrid fuzzy soft sets decision making method in medical diagnosis IEEE. Access 6:25300–25312

    Google Scholar 

  • Yang Y, Wang J-Q (2018) SMAA-based model for decision aiding using regret theory in discrete Z-number context. Appl Soft Comput 65:590–602

    Google Scholar 

  • Yager RR (1979) Ranking fuzzy subsets over the unit interval. In: 1978 IEEE conference on decision and control including the 17th symposium on adaptive processes. https://doi.org/10.1109/CDC.1978.268154

  • Yazdanparast R, Tavakkoli-Moghaddam R, Heidari R, Aliabadi L (2018) A hybrid Z-number data envelopment analysis and neural network for assessment of supply chain resilience: a case study. Central Eur J Oper Res. https://doi.org/10.1007/s10100-018-0596-x

    Article  Google Scholar 

  • Zadeh LA (1965) Fuzzy Sets. Inf Control 8:338–353

    MATH  Google Scholar 

  • Zadeh LA (2011) A note on Z-numbers. Inf Sci 181:2923–2932

    MATH  Google Scholar 

  • Zhou X, Xu Z (2018) An integrated sustainable supplier selection approach based on hybrid information aggregation. Sustainability 10:2543

    Google Scholar 

  • Zhu K, Shen J, Yao X (2019) A three-echelon supply chain with asymmetric information under uncertainty. J Ambient Intell Human Comput 10:579–591

    Google Scholar 

Download references

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Authors and Affiliations

  1. Department of Industrial Engineering, Iran University of Science and Technology, Tehran, 16846-13114, Iran

    Ali Reza Hoseini, Seyed Farid Ghannadpour & Roya Ghamari

Authors
  1. Ali Reza Hoseini
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  2. Seyed Farid Ghannadpour
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  3. Roya Ghamari
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Correspondence to Seyed Farid Ghannadpour.

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Appendix

Appendix

See Tables 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30.

Table 19 Linguistic terms determined by DM2
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Table 20 Linguistic terms determined by DM3
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Table 21 Linguistic terms determined by DM4
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Table 22 The converted Z-numbers substituted with corresponding linguistic terms for DM2
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Table 23 The converted Z-numbers substituted with corresponding linguistic terms for DM3
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Table 24 The converted Z-numbers substituted with corresponding linguistic terms for DM4
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Table 25 The obtained performance criteria and enabler weights for 10 suppliers by DM2
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Table 26 The obtained performance criteria and enabler weights for 10 suppliers by DM3
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Table 27 The obtained performance criteria and enabler weights for 10 suppliers by DM4
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Table 28 The obtained performance criteria weights for 10 DM2
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Table 29 The obtained performance criteria weights for 10 DM3
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Table 30 The obtained performance criteria weights for 10 DM4
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Hoseini, A.R., Ghannadpour, S.F. & Ghamari, R. Sustainable supplier selection by a new possibilistic hierarchical model in the context of Z-information. J Ambient Intell Human Comput 11, 4827–4853 (2020). https://doi.org/10.1007/s12652-020-01751-3

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