Improvement and Application of Intelligent Algorithm for urban E-commerce Logistics Distribution Path Planning

Against the backdrop of booming e-commerce, urban logistics and distribution are facing increasingly severe challenges such as high costs and low efficiency. This paper first analyzes the existing intelligent algorithms for logistics and distribution path planning, and then proposes an improved algorithm by integrating advanced optimization techniques, adjusting algorithm parameters, and introducing new heuristic rules to design a more efficient search mechanism. Through these improvements, the algorithm aims to achieve lower costs, shorter delivery times, and higher vehicle utilization. Experimental studies have shown that the improved algorithm performs well in multi-objective optimization. The improved CIPSO-LR algorithm performs well in multi-objective optimization: The total cost is 134.06, which is 22.1% lower than the baseline algorithm. The optimal granularity is 5m. The path length is 1340.49m, which is shorter than other algorithms. The vehicle utilization rate reaches 92.3%, which is higher than traditional PSO, ACO and GA algorithms. The calculation time is only 8.9s, and the calculation efficiency is the highest among the compared algorithms. These show that the algorithm proposed in this paper is significantly better than the traditional algorithm in all aspects, proving its effectiveness in practical applications.