A critical review of the application of multi-criteria decision-making in the sustainability assessment of biorefineries

This review assesses peer-reviewed journal papers (from Scopus and Web of Science databases) that document the use of multi-criteria decision-making (MCDM) to address challenges related to biorefineries. The overarching goal is to find common trends in the application of MCDM methods to biorefinery systems and check for knowledge gaps. The 61 original peer-reviewed papers published between 2010 and 2024 were categorized into four groups (facility siting, material selection, process evaluation, and supply chain) to enable an equitable and easy comparison of the published works. Furthermore, 7 review papers were assessed separately. Our review suggests that of the three pillars of sustainability (economic, environmental, and social), the social pillar is the least considered. Experts’ opinions and literature are the most used data sources for the importance of/trade-off between criteria and the performance of alternatives, respectively. Authorities and government representatives are considered less often as decision makers, which may lead to the proposal of infeasible alternatives in terms of regulations and policies. Concerning MCDM methods, the analytical hierarchy process (AHP) and its fuzzy version are the most common weighting methods, the weighted sum method (WSM) is the most common aggregation method, and min-max normalization is more common than vector normalization. Finally, the use of Monte-Carlo simulation as a means of sensitivity analysis is rare in this field, and deterministic methods are more common. • Process evaluation is most prevalent in multi-criteria decision making studies. • Second and third-generation biorefineries are assessed in a minority of studies. • Social indicators are least prevalent in multi-criteria decision making studies. • Subjective weights, linear normalization, and the weighted sum method are used most. • Sensitivity analysis and stochastic methods are rare and may improve future studies.