BiAPPSS: an enhanced bipolar fuzzy APPSS framework for sustainable solid waste management

Introduction Selecting suitable sites for solid waste management (SWM) facilities is a complex decision-making problem involving conflicting socio-geographical criteria and inherent uncertainty. Method To address this challenge, this study proposes a novel Bipolar Association between Preference and Performance with Satisfactory Score (BiAPPSS) framework by extending the classical APPSS model into a bipolar triangular fuzzy environment. The proposed approach simultaneously captures supportive and conflicting assessments through positive and negative membership degrees, enabling a more realistic evaluation of alternative locations. Furthermore, a Bidirectional Associative Memory (BAM) network is integrated to model the interrelationships between evaluation criteria and suitable regions, enhancing the interpretability of the decision process. Results and Discussion The applicability of the BiAPPSS–based framework is demonstrated through a real-world case study on SWM site selection in Ernakulam district, Kerala, India, where Brahmapuram is identified as the most suitable location. The robustness and validity of the proposed model are verified using comparative analysis with existing fuzzy MCDM methods, sensitivity analysis, and interpretability assessment. The results indicate that the proposed framework provides a reliable and data-driven decision-support tool for sustainable SWM planning and policy formulation.