Evaluating municipal solid waste management with a confidence level-based decision-making approach in q-rung orthopair picture fuzzy environment

Municipal solid waste (MSW) management is a critical aspect of urban planning and public health. As societies strive towards environmental sustainability and socio-economic development, robust techniques to transform waste into energy become paramount. Assessment of waste-to-energy (WTE) techniques is based on a spectrum of criteria that are often vague and imprecise. The current study addresses this multi-criteria group decision-making problem of assessing and evaluating WTE methods for MSW management using q-rung orthopair picture fuzzy (qRPF) numbers. The study proposes an innovative combination of the Defining Interrelationships Between Ranked-criteria (DIBR) and Compromise Ranking of Alternatives from Distance to Ideal Solution (CRADIS) methods. The criteria are assessed using the recently developed DIBR method, while the alternatives are assessed using a popular distance-based method, namely CRADIS. Moreover, new confidence level-based aggregation operators for qRPF numbers are proposed and used to aggregate fuzzy data, while a novel triangular divergence-based distance measure is proposed and used to modify the existing CRADIS method. The results show that anaerobic digestion and pyrolysis are the two most preferred WTE methods for MSW management. An extensive comparative analysis demonstrates the applicability of the proposed methodology, while an exhaustive sensitivity analysis confirms the proposed method’s stability. The results of Spearman’s correlation coefficient validate the model’s practicality. The findings of this research yield significant insights beneficial to policymakers, industry stakeholders, and researchers alike. By implementing sustainable waste management strategies, municipalities can improve recycling rates, minimize landfill use, and promote a cleaner, healthier environment for urban populations.