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Research on Dynamic Division Method of Distribution Area under Big Data Environment

There are path planning issues under restrictions such as time windows when the express delivery point is delivered, and the delivery address of express parcels in actual delivery may be scattered. The volume of express parcels is extremely uneven for the express delivery point. When the amount of express delivery exceeds the load of the express delivery point too much, pure path planning becomes meaningless. Therefore, considering the actual situation and taking the distribution route and the maximum delivery volume of the express point as the main constraints, a possible route planning is conducted in the paper according to the express delivery address before the distribution point enters the express point. Then, based on the big data of the Internet of Things, the distribution area of the express delivery point is dynamically divided, and the express delivery that meets the maximum delivery volume and optimal route planning is allocated to the corresponding neighboring express delivery points. Moreover, the overall equilibrium optimization of each express delivery point is performed to obtain the final dynamically divided distribution area. Experiments have proved that the optimization algorithm in the paper has higher calculation accuracy than other methods, which can achieve more efficient arrangements for the division of logistics distribution areas and improve the distribution rate of load balancing and the quality of delivery services.