Research on Dispatching Model of Disaster Victims Based on Hybrid Optimization Algorithm Under Aviation Emergency Rescue System

In this paper, the optimization problem of helicopter dynamic scheduling in the construction of China's aviation emergency rescue system is studied. Aiming at the capacity shortage and the demand for multi-stage revisiting of the affected sites in the initial post-disaster rescue scenario, a helicopter dynamic scheduling model integrating the multi-dimensional constraints of “priority-path” is constructed. A two-layer chromosome coding architecture is innovatively designed, and a hybrid optimization algorithm (GA-ALNS) integrating genetic algorithm (GA) and adaptive large neighborhood search (ALNS) is proposed to effectively coordinate global search and local optimization. Experimental studies show that compared with the traditional genetic algorithm (GA), particle swarm algorithm (PSO) and gray wolf optimization algorithm (GWO), GA-ALNS achieves an average convergence value close to the set optimal solution of 95.18% in 50 rounds of experiments, and outperforms the selected traditional algorithms in terms of the overall solution results. The research results provide a new method with engineering practical value for the dispatching of disaster victims in emergency rescue scenarios.