An improved consistency optimization model and VIKOR approach for supplier selection of port shipping equipment under fuzzy and stochastic environments

Lian, Xiaozhen, Luo, Xinyi, Su, Deying and Liu, Ying ORCID: https://orcid.org/0000-0001-9319-5940 2026. An improved consistency optimization model and VIKOR approach for supplier selection of port shipping equipment under fuzzy and stochastic environments. International Journal of Fuzzy Systems Item availability restricted.

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Abstract

The promotion of sustainability in the port shipping industry is crucial for improving production efficiency and accelerating the modernization of port shipping equipment (PSE). The latter process necessitates selecting an optimal PSE supplier. However, due to the uncertainty of supplier evaluation, supplier selection of PSE becomes a complicated fuzzy multiple criteria decision-making (MCDM) problem, which includes the fuzzy criteria and stochastic criteria (FCSC). While the application of MCDM approaches to PSE supplier selection has been widely reported in recent years, most studies only consider either stochastic criteria or fuzzy criteria based on stochastic dominance rules or interval-valued intuitionistic fuzzy set (IVIFS) theory. Consequently, the complexity of supplier selection under the mixed uncertainty of FCSC trade-offs remains unresolved. This paper presents an improved multi-criteria optimization and compromise solution (VIKOR) method that integrates FCSC. In this method, the theories of IVIFS and of stochastic dominance rules are applied to address the FCSC, a nonlinear consistency optimization model is constructed to derive the criteria weights for FCSC, and the superiority ranking of alternative PSE suppliers is conducted based on an improved VIKOR framework. Moreover, method comparisons and sensitivity analyses are elaborated through a real-world case study of PSE supplier selection. Finally, comparative analysis with traditional methods reveals the effectiveness of the proposed approach.

Item Type:	Article
Status:	In Press
Schools:	Schools > Engineering
Publisher:	Springer
ISSN:	1562-2479
Date of First Compliant Deposit:	9 March 2026
Date of Acceptance:	18 January 2026
Last Modified:	09 Mar 2026 15:15
URI:	https://orca.cardiff.ac.uk/id/eprint/185624

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