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Nuclear energy is one of the most economical, environmentally friendly, and efficient energy sources. However, the development and utilization of nuclear energy also have significant risks, the most typical of which is the occurrence of nuclear accidents. The radiation release caused by nuclear leakage will seriously affect the personal safety of surrounding residents. Vehicle evacuation is one of the effective methods of large-scale evacuation. A vehicle scheduling optimization model based on the dual constraints of tin1e and exposure dose is proposed in this paper for the uncertainties of road resistance, dose field variation, and personnel distribution in real scenarios. The road resistance formula is introduced to modify the vehicle travel time, and the dose field is meshed to realize a real-time update of the dose rate. A genetic algorithm solves the model to obtain vehicle quantity allocation and route arrangement. The model reasonably arranges vehicle schedules and routes to assist in emergency decision-making. With the actual data of the Fuqing Nuclear Power Plant in China, the case demonstrates that the evacuation time and exposure dose are reduced by 44.17% and 40.22%, respectively, compared with the traditional solution. This research improves the safety performance of nuclear power and promotes the sound development of nuclear power.
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