The optimal placement of railway maintenance depots is a critical, yet complex, component of modern transport system planning, with significant implications for operational efficiency, cost management and network reliability. This study introduces a decision-support model that integrates the picture fuzzy (PiF) analytic hierarchy process and the PiF evaluation based on distance from average solution to evaluate candidate depot locations under uncertainty. Applied to the metropolitan railway network in Istanbul, the proposed model incorporates quantitative and qualitative criteria, including cost, accessibility, operational capability, environmental resilience and social factors. The results indicate that cost-related aspects and travel time exert the most significant influence on depot site selection, whereas social factors play a secondary role. The proposed framework enables planners to systematically assess alternative sites and supports the adoption of advanced computational methods in transport infrastructure planning. Overall, this research provides actionable guidance for practitioners and highlights the value of uncertainty-aware, multi-criteria approaches in technology-driven transport system development. The findings align with UN Sustainable Development Goals 9 (Industry, Innovation and Infrastructure) and 11 (Sustainable Cities and Communities) by promoting resilient transport infrastructure.
Köse et al. (Thu,) studied this question.