Green Supplier Evaluation and Selection Based on Bi-Directional Shapley Choquet Integral in Interval Intuitive Fuzzy Environment

Wenkun Zhou and Yitao Gu ()
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Wenkun Zhou: School of Management, Shanghai University, Shanghai 200444, China
Yitao Gu: School of Management, Shanghai University, Shanghai 200444, China

Sustainability, 2025, vol. 17, issue 7, 1-32

Abstract: The evaluation and selection of green suppliers is an important way for enterprises to maintain sustainable development and help them reduce costs and increase efficiency. This paper proposes a multi-criteria decision-making (MCDM) model in an interval intuitive fuzzy environment. This model uses interval-valued intuitive uncertainty language number (IVIULN) to describe expert evaluation of qualitative indices. Expert weights are determined through expert social networks, and an improved aggregation operator is proposed to aggregate the evaluation information. The proposed operator can ensure the stability of the results even in the case of extreme values. Subsequently, considering a large number of mutually related indices, a novel teaching-learning-based optimization (NTLBO) algorithm is used to identify the value of λ -fuzzy measures. This algorithm improves the teaching stage and proposes the idea of teaching students in accordance with their aptitude, introduces precision parameters, and adds a self-study stage. It has been verified by numerical examples that it is far superior to commonly used heuristic algorithms in terms of algorithm accuracy and run time. Finally, the alternatives are ranked by bi-direction Shapley–Choquet integral. The model’s effectiveness is demonstrated through a case study. This paper also examines the impact of key parameters on the results through sensitivity analysis.

Keywords: multi-criteria decision-making (MCDM); interval-valued intuitive uncertainty language number; aggregation operator; teaching-learning-based optimization algorithm; Choquet integral (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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