Abstract: The complexity and uncertainty of unexpected events pose higher requirements for dynamic planning of logistics distribution paths and flexible formulation of solutions. To quantify the immediate characteristics of emergencies, strategies for detours, slowdowns, and suspensions were designed, and a dynamic path planning model was constructed that includes vehicle transportation costs, distribution center maintenance costs, and additional delivery timeout costs; Secondly, 9 random combinations of destruction and repair operators were constructed to improve individuals, and a hybrid genetic large neighborhood search (GA-LNS) algorithm was designed to solve the model. The research results indicate that in typical scenarios, dynamic schemes only increase the total cost by 2.62% compared to static models. The applicability analysis of dynamic path planning shows that when the impact range of sudden events is less than 2 km, there is no significant difference in the total cost between slow and detours; When the impact range is greater than 2 km, the total cost of the detour strategy is significantly better than that of the slow-moving strategy, with a maximum cost difference of 500 yuan. This method effectively enhances the resilience of emergency logistics by dynamically balancing time costs, operational costs, and path reliability, providing support for real-time decision-making scenarios such as urban emergency distribution and medical material scheduling.

Key words:

text-indent:0cm, "> logistics engineering, route planning, multi-objective optimization, unexpected disruptions, large neighborhood search (LNS) algorithm