Spatial optimization methods for waste-to-energy facility siting: a review of GIS-MCDA approaches

Abstract

Municipal solid waste (MSW) management remains a critical challenge in rapidly urbanizing regions, where sustainable alternatives to landfilling are urgently required. Waste-to-Energy (WtE) systems provide a viable pathway for energy recovery and waste volume reduction; however, effective facility siting is essential to ensure environmental compliance, economic viability, and social acceptability. This study presents a systematic review of the integration of Geographic Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA) for spatial planning and optimization of WtE facilities. Following PRISMA guidelines, 54 peer-reviewed studies published between 2015 and 2025 were screened, of which 35 spatial GIS–MCDA case studies formed the basis of quantitative synthesis. The geographic distribution of spatial applications reveals concentration in Asia (40%), followed by Europe (23%), Latin America (17%), Africa (11%), North America (6%), and multi-regional studies (3%). Methodologically, deterministic Analytic Hierarchy Process (AHP)-based frameworks dominate (74%), while fuzzy AHP extensions account for 14%. Hybrid MCDA–optimization models represent only 6%, and AI-integrated approaches just 3%, indicating limited adoption of advanced system-level integration. Environmental criteria are incorporated in 97% of studies, logistics factors in 91%, economic considerations in 86%, and technical parameters in 80%, whereas policy and social criteria appear in only 60%, highlighting an imbalance between ecological screening and institutional integration. The synthesis identifies key research gaps, including a lack of standardized criteria hierarchies, limited lifecycle techno-economic modeling, insufficient structured stakeholder participation, and underutilization of hybrid optimization and artificial intelligence tools. The findings suggest that GIS–MCDA research in WtE siting remains predominantly at the suitability screening stage, with a gradual but incomplete transition toward integrated, data-driven planning frameworks. Advancing toward multi-objective optimization, dynamic spatial analytics, and participatory decision-support architectures will be essential for strengthening sustainable and resilient WtE infrastructure planning.