Proposal of a multi-expert multi-criteria model for the sustainability assessment of industrial systems under uncertainty

Incorporating sustainability into industries is crucial to achieving sustainable development of industrial systems. However, identifying the most sustainable industrial system among multiple alternatives is a challenging task, especially when conflicting criteria and different experts are involved. This challenge is compounded by existing uncertainties within the knowledge and available data, making it even more difficult to ensure accuracy and fairness in decision-making. This study proposes a multi-expert multi-criteria model with interval numbers for the sustainability assessment of industrial systems. The model incorporates an interval group full comparison method to determine criteria weights and an interval gray relational projection to rank alternatives, thus achieving justice in weight aggregation under epistemic uncertainty and improving the reliability of alternatives prioritization by considering the relationships and balance among multiple criteria under data uncertainty. Through a case study on renewable energy-driven desalination systems and five analytic items, the effectiveness and advantages of this model were confirmed. Compared to the previous studies, this work could enhance the functionality of MCDM-based sustainability assessment by reaching a consensus in group decisions and providing a reliable ranking result under uncertainty.Graphical abstractA multi-expert multi-criteria model for the sustainability assessment of industrial systems