Study on intelligent assessment of hazardous chemical leakage risk and optimization model of emergency response

This study aims to build a logistics system monitoring and optimization model based on intelligent algorithm to improve the efficiency and accuracy of logistics security management. The model focuses on item leakage events in the logistics process, and applies linear programming optimization algorithm to design risk assessment and emergency response strategies through comprehensive consideration of several factors such as item characteristics, leakage scale, environmental impact and emergency evacuation path. The model simulates different leakage scenarios, generates specific emergency evacuation plans, and optimizes the evacuation path and time. Simulation results show that the proposed model can significantly improve the efficiency of emergency response, reduce the possibility of secondary disasters, and ensure safety. Data analysis further verifies the robustness and applicability of the model in different scenarios. This study provides a new idea for intelligent logistics management, which not only has important theoretical significance, but also provides technical support for practical safety management.