Optimization of Warehousing and Distribution Paths Based on Particle Swarm Optimization

In view of the inefficiency of traditional algorithms in dealing with large-scale distribution path problems, this paper designs a warehouse distribution path optimization method based on particle swarm optimization (PSO) to optimize the search mechanism. By introducing an adaptive inertia weight adjustment strategy, experimental results show that the warehouse space utilization rate of the PSO algorithm is above 90%, and its speed is also better than traditional genetic, ant colony and simulated annealing algorithms. The research provides a more efficient solution for warehouse distribution systems and has practical application potential.