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A novel supplier selection method that integrates the intuitionistic fuzzy weighted averaging method and a soft set with imprecise data

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  • Kuei-Hu Chang

    (R.O.C. Military Academy)

Abstract

Along with advances in technology and the advent of the information age, supply chain competition will become the core strategy of enterprises that are in pursuit of a competitive advantage. Supplier selection and evaluation are key issues in the success of a competitive enterprise. Supplier selection for an enterprise is a typical multicriteria decision-making problem that includes qualitative and quantitative criteria. However, some input information can be missing or nonexistent in selecting suppliers, rendering it more difficult to choose the best supplier. To this end, the traditional supplier selection approach does not consider the ordered weights of the values of attributes, causing biased conclusions. Moreover, there is a significant amount of fuzzy and intuitionistic fuzzy information in real-world situations, for which the traditional approach in choosing the best supplier becomes no longer applicable. To solve these issues, this study proposes a novel supplier selection method, integrating the intuitionistic fuzzy weighted averaging method and the soft set with imprecise data, in identifying the best supplier in a supply chain. To illustrate our proposed method, a numerical example of the supplier selection problem is adopted. This paper also compares the results of the fuzzy weighted averaging, intuitionistic fuzzy weighted averaging, and intuitionistic fuzzy dependent aggregation operator methods in dealing with missing or nonexistent data. Based on our results, the proposed method is reasonable, effective, and better reflects real-world situations with regard to supplier selection.

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  • Kuei-Hu Chang, 2019. "A novel supplier selection method that integrates the intuitionistic fuzzy weighted averaging method and a soft set with imprecise data," Annals of Operations Research, Springer, vol. 272(1), pages 139-157, January.
    • Handle: RePEc:spr:annopr:v:272:y:2019:i:1:d:10.1007_s10479-017-2718-6
    DOI: 10.1007/s10479-017-2718-6
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    References listed on IDEAS

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    1. Chan, Felix T.S. & Kumar, Niraj, 2007. "Global supplier development considering risk factors using fuzzy extended AHP-based approach," Omega, Elsevier, vol. 35(4), pages 417-431, August.
    2. Kannan Govindan & R. Sivakumar, 2016. "Green supplier selection and order allocation in a low-carbon paper industry: integrated multi-criteria heterogeneous decision-making and multi-objective linear programming approaches," Annals of Operations Research, Springer, vol. 238(1), pages 243-276, March.
    3. Kuei-Hu Chang, 2016. "A novel reliability allocation approach using the OWA tree and soft set," Annals of Operations Research, Springer, vol. 244(1), pages 3-22, September.
    4. Sujeet Kumar Singh & Shiv Prasad Yadav, 2016. "A new approach for solving intuitionistic fuzzy transportation problem of type-2," Annals of Operations Research, Springer, vol. 243(1), pages 349-363, August.
    5. Kuei-Hu Chang & Yung-Chia Chang & Kai Chain & Hsiang-Yu Chung, 2016. "Integrating Soft Set Theory and Fuzzy Linguistic Model to Evaluate the Performance of Training Simulation Systems," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-29, September.
    6. Kannan Govindan & R. Sivakumar, 2016. "Green supplier selection and order allocation in a low-carbon paper industry: integrated multi-criteria heterogeneous decision-making and multi-objective linear programming approaches," Annals of Operations Research, Springer, vol. 238(1), pages 243-276, March.
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    Cited by:

    1. Sirin Suprasongsin & Pisal Yenradee & Van-Nam Huynh, 2020. "A weight-consistent model for fuzzy supplier selection and order allocation problem," Annals of Operations Research, Springer, vol. 293(2), pages 587-605, October.
    2. Hakan Gökhan Gündoğdu & Ahmet Aytekin & Şura Toptancı & Selçuk Korucuk & Çağlar Karamaşa, 2023. "Environmental, social, and governance risks and environmentally sensitive competitive strategies: A case study of a multinational logistics company," Business Strategy and the Environment, Wiley Blackwell, vol. 32(7), pages 4874-4906, November.
    3. Wei Xu & Hongyong Fu & Huanpeng Liu, 2019. "Evaluating the Sustainability of Microfinance Institutions Considering Macro-Environmental Factors: A Cross-Country Study," Sustainability, MDPI, vol. 11(21), pages 1-22, October.
    4. Mehdi Rajabi Asadabadi & Hadi Badri Ahmadi & Himanshu Gupta & James J. H. Liou, 2023. "Supplier selection to support environmental sustainability: the stratified BWM TOPSIS method," Annals of Operations Research, Springer, vol. 322(1), pages 321-344, March.
    5. Erfan Babaee Tirkolaee & Zahra Dashtian & Gerhard-Wilhelm Weber & Hana Tomaskova & Mehdi Soltani & Nasim Sadat Mousavi, 2021. "An Integrated Decision-Making Approach for Green Supplier Selection in an Agri-Food Supply Chain: Threshold of Robustness Worthiness," Mathematics, MDPI, vol. 9(11), pages 1-30, June.
    6. Kuei-Hu Chang, 2022. "A novel reliability calculation method under neutrosophic environments," Annals of Operations Research, Springer, vol. 315(2), pages 1599-1615, August.
    7. Federico Toffano & Michele Garraffa & Yiqing Lin & Steven Prestwich & Helmut Simonis & Nic Wilson, 2022. "A multi-objective supplier selection framework based on user-preferences," Annals of Operations Research, Springer, vol. 308(1), pages 609-640, January.

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