Logistics scheduling method and device

Abstract

The invention relates to the technical field of intelligent scheduling, in particular to a logistics scheduling method and device, and the method comprises the steps: obtaining a plurality of deliverymen to be scheduled and a plurality of orders to be distributed; for each deliveryman, obtaining an influence factor related to the deliveryman; determining a relationship weight between the deliveryman and each order based on the influence factor; determining an optimal order assignment scheme by adopting a bipartite graph matching algorithm based on the relationship weight, and matching each order in the optimal order assignment scheme with the deliveryman; and for each order, assigning the order to a deliveryman matched with the optimal order assignment scheme in the optimal order assignment scheme. According to the logistics scheduling method, the relationship weight between the deliveryman and each order is determined through the influence factors related to the deliveryman, and the bipartite graph matching algorithm is adopted to determine the optimal order assignment scheme based on the relationship weight, so that the matching success rate and the logistics scheduling efficiency can be improved.

Description

technical field [0001] The invention relates to the technical field of intelligent scheduling, in particular to a logistics scheduling method and device. Background technique [0002] Freight logistics is a relatively complex branch of the logistics industry, involving major links such as trunk logistics and urban short-haul logistics. Among them, urban short barge logistics has attracted much attention because it involves more scheduling and loading issues. The urban short-haul logistics scheduling problem is a complex matching problem with multiple objectives and multiple constraints considering many factors such as transportation time, vehicle loading, destination, transportation route, carpooling at different destinations, and cost control. [0003] The existing scheduling methods of urban short-haul logistics are mostly manual scheduling, that is, each scheduling personnel organizes the capacity offline according to the orders of the day, and manually weighs and decide...

AI Technical Summary

Problems solved by technology

[0004] 1) The scheduling pressure of logistics vehicles is high. In the actual scheduling, it is necessary to consider not only customer demand satisfaction, deployable resources (number of vehicles), loading rate, and delivery time, but also loading combinations, earliest available time, and long-term and short-term carpooling. and other constraints, the required processing speed and precision have put a lot of pressure on the dispatchers, who are difficult to give a scheduling plan in a short period of time, and the scheduling efficiency is low and the scheduling results are prone to non-optimal situations;

[0005] 2) Customer satisfaction is low. Existing orders have many distribution points and a small amount of delivery. It often takes a long time to ship a full vehicle, resulting in an excessively long order arrival time, which affects the completion of Order to Delivery (OTD). rate, affecting customer satisfaction

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