Ensuring environmental sustainability has become a pressing global concern, leading to an increasing demand for efficient waste management solutions. Among these, the recycling of end-of-life tires (ELTs) presents both an opportunity and a challenge due to its environmental and economic implications. As the recycling of ELTs becomes mandatory in many countries, decision-makers must carefully evaluate and select suitable facility features during the installation process. Given the complexity and the multiple factors involved in facility selection, this problem is best approached using multi-criteria decision-making (MCDM) methods. In this study, a novel hybrid decision-making framework is proposed, integrating the interval-valued Pythagorean fuzzy Criteria Importance Through Intercriteria Correlation (CRITIC) and Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) methods to address the ELT facility selection problem. The CRITIC method was employed to objectively determine the importance of weights of twelve evaluation criteria. The results indicate that Monthly Electricity Cost (C5) is the most influential criterion, followed by ELT Facility Capacity (C1) and Carbon Black Conversion Percentage (C4), while Monthly Labor Cost (C6) has the lowest impact. Based on the MARCOS method, the recycling alternatives were ranked as A > B > D > C, identifying Alternative A as the most suitable option. While extensive research has been conducted on fuzzy MCDM approaches, no studies have yet incorporated interval-valued Pythagorean fuzzy sets (IVPFNs) within the CRITIC-MARCOS framework for ELT recycling. This study bridges this gap by presenting an innovative method that effectively handles uncertainties in decision-making. The proposed approach enhances decision accuracy by considering both the importance of evaluation criteria and the optimal ranking of alternatives. The results provide a robust and systematic methodology for selecting the most appropriate ELT recycling facility, contributing to both sustainability and efficient resource utilization.
Gülçin Canbulut (Sat,) studied this question.