To improve the logistics efficiency and economy, one of the key measures is to optimize the delivery path and the allocation of resources. Delivery cost, delivery time and resource utilization are important indicators to measure the effectiveness of this optimization. The paper chooses Ant Colony Optimization (ACO) as the research object, studies the performance of ACO in the optimization of delivery path and resource allocation of shared logistics express platform and compares it with Particle Swarm Optimization (PSO) in the experimental part. The ACO algorithm is optimized by the ant colony behavior pattern in path planning and resource allocation, while the PSO algorithm is optimized by simulating the collaborative search behavior of the particle swarm. The experimental results show that the two algorithms both contribute to the reduction of delivery cost and delivery time. The results of cost and time are gestated in the results of resource utilization. In terms of resource utilization, PSO has a utilization rate between 93 and 99%, which is 3% higher at least and 4% higher at most than ACO, and the Resource utilization is lower, which means that the performance of PSO algorithm is better than that of ACO.