Optimization of heterogeneous emergency resources deployment considering road segment criticality under adverse weather

The effective deployment of emergency resources under adverse weather is critical for maintaining road network functionality and enhancing transportation resilience. However, the spatial heterogeneity of road segment criticality poses a significant challenge to efficient resource deployment. To address this challenge, this study integrates road segment criticality into the emergency resource deployment process. Specifically, road segment criticality is quantified by integrating functional, structural, and resilience-based metrics, and synthesized using an entropy-weighted method. Subsequently, a multi-objective optimization model for heterogeneous emergency resource deployment is formulated, accounting for road segment criticality and the operational characteristics of resources across distinct response phases. The model aims to achieve three objectives: minimizing construction costs, maximizing road network accessibility, and ensuring effective coverage of critical road segments. The performance of the model is evaluated through a case study on Beijing's inner 4th Ring Road under adverse weather conditions. The effects of criticality thresholds, coverage distance, and facility capacity are further investigated through computational experiments. Results demonstrate that, compared to the baseline model that excludes segment criticality, the proposed criticality-based model reduces the number of facilities by 7.27 % while the compromise solution increases the coverage of critical road segments by 32.53 %. These findings emphasize that incorporating road segment criticality into the deployment model leads to more balanced and efficient resource allocation strategies.