Post-Disaster rescue route formation based on optimized dynamic programming algorithm

This study proposes a disaster rescue path optimization algorithm integrating dynamic programming and priority queue, and analyzes the impact of this algorithm on rescue efficiency under different node reward distributions (uniform/normal) through earthquake and flood scenario simulations. The algorithm eliminates redundant computation through dynamic programming to ensure rescue reward uniqueness and path optimization. Experiments show that the algorithm significantly reduces the path cost under the premise of guaranteeing the rescue reward threshold: e.g. 48 cost/100.77 reward is realized under the normal distribution of the earthquake scenario, which is significantly improved compared with the traditional greedy strategy (94 cost/96.45 reward).