Sustainable Flood Emergency Material Demand Grading and Routing Re-Optimization: A Game-Theoretic Combined Weighting and Grey-TOPSIS Approach in Jiaozuo, China

Abstract

Abstract

Timely, differentiated distribution of emergency materials reduces flood losses and supports resilient, sustainable cities, and yet demand urgency is rarely quantified jointly with routing. We propose an integrated framework combining game-theoretic AHP–CRITIC weighting, grey relational TOPSIS, exact Fisher–Jenks partitioning, and demand-driven ant colony routing applied to Jiaozuo’s July 2021 “7·20” flood in China. Demand urgency indices for eleven areas span 0.3064–0.6020 and are divided by exact Fisher–Jenks optimization into four grades mapping onto China’s four-tier emergency response system; the grades are robust across weighting schemes (identical under CRITIC-only and equal weights, with only two one-grade shifts under AHP-only weights) and stable under bootstrap perturbation. The routing model incorporates an edge risk exposure term; the optimal route trades an 8.0% increase in adjusted distance for a 6.1% reduction in urgency-weighted delivery time (F* = 235.8774), meeting the local 6 h first-wave dispatch target. At a matched evaluation budget, the improved and standard ant colony algorithms tie in solution quality, and both significantly outperform the genetic and particle swarm algorithms (p < 0.001). Robustness holds across weighting schemes, detour factors, and bootstrap perturbations, supporting resource-efficient, disaster-resilient emergency logistics (SDG 11.5).