A new fuzzy-stochastic compromise ratio approach for green supplier selection problem with interval-valued possibilistic statistical information

Organizations must regard environmental and green concepts in their decision-makings and all of the significant tasks in supplier selection process for the supply chain. For this purpose, the evaluation of conflicting criteria with environmental and conventional approaches can be simultaneously considered in the green supplier selection problem (GSSP). This paper introduces a novel group decision-making process with Monte Carlo simulation under interval-valued fuzzy and stochastic environments for solving the GSSPs. The proposed compromise ratio model includes some main phases: (1) weighting and rating phase, (2) aggregating phase, (3) simulating phase, and (4) ranking phase. New separation measure matrixes are developed with an interval-valued fuzzy possibilistic statistical approach. Then, new distinguish indexes and new final score index are presented to indicate the last inclination arrangement of green supplier candidates. An application example in the GSSP is provided from the recent literature to show the applicability of proposed interval-valued fuzzy-stochastic group decision model. Finally, a comparative analysis is conducted to highlight the advantages of the model in comparison with similar decision methods.