The location selection of logistics and storage center fundamentally determines the distance between the origin and arrival of goods, which is directly related to whether goods can be transported in a timely and efficient manner, as well as whether distribution costs and storage costs can be minimized. Traditional logistics and warehousing center location solving algorithm is divorced from practical application, and prone to local optimization, slow solving speed and single attention and other problems. In order to reduce the logistics delivery time and logistics cost, and put forward a practical solution for location selection, this paper studied the location selection of logistics storage center in Beijing-Tianjin-Hebei region by improving k-means clustering algorithm and monarch butterfly optimization algorithm. Experimental simulation results show that compared with other optimization algorithms, the improved Monarch optimization algorithm has advantages in solving accuracy, convergence speed and iteration times, and can effectively complete the site selection of logistics storage center, effectively shorten the distance of logistics distribution and improve the efficiency of logistics distribution.