Logistics Network Parcel Emergency Dispatch and Structural Optimization Model

This paper focuses on optimizing parcel logistics in e-commerce networks during emergencies. The research introduces innovative methods, including BP neural network prediction model, simulated annealing algorithm and Dijkstra algorithm, to improve prediction accuracy and adaptability in complex logistics networks. The study also incorporates the entropy weight Topsis method to evaluate logistics nodes and routes. By simulating real-world scenarios, the study proposes practical logistics network optimization strategies to solve future industry challenges.