Order picking task generation method and device, storage medium and electronic equipment

Abstract

The invention relates to a an orderpicking task generationg method and device, a storage medium and electronic equipment, and the method comprises the steps: determining picking information corresponding to each cargo in a plurality of target orders; for any two pieces of picking information in the plurality of pieces of picking information, according to a preset position corresponding relationship, determining a first distance of a storage position where goods respectively corresponding to the any two pieces of picking information are located and a second distance of a picking storage position respectively corresponding to the any two pieces of picking information; wherein the picking storage position is the position where the goods corresponding to the same flat cable information are stored after picking is completed; for each piece of picking information in the plurality of pieces of picking information, determining a third distance between the storage position of the goods corresponding to the picking information and the picking storage position corresponding to the picking information according to a preset position corresponding relationship; and generating a picking task according to the picking information, the first distance, the second distance and the third distance corresponding to the plurality of target orders.

Description

technical field [0001] The present disclosure relates to the field of order picking, and in particular, to a method, device, storage medium and electronic equipment for generating a picking task. Background technique [0002] In the warehousing and distribution business scenario under the B2B business model, the customer places an order before the order deadline. After the order deadline, the warehouse distribution management system can arrange the delivery route according to the order delivery address (that is, the line arrangement stage). After the line arrangement is completed, Picking tasks can be generated according to the order requirements in the wiring line, and then the warehouse distribution staff can pick according to the picking tasks, so that the goods can be delivered after the picking is completed. In this business scenario, the generated picking tasks Whether the task is reasonable or not will directly affect the picking efficiency of the staff. [0003] The...

AI Technical Summary

Problems solved by technology

[0002] In the warehousing and distribution business scenario under the B2B business model, the customer places an order before the order deadline. After the order deadline, the warehouse distribution management system can arrange the delivery route according to the order delivery address (that is, the line arrangement stage). After the line arrangement is completed, Picking tasks can be generated according to the order requirements in the wiring line, and then the warehouse distribution staff can pick according to the picking tasks, so that the goods can be delivered after the picking is completed. In this business scenario, the generated picking tasks Whether the task is reasonable or not will directly affect the picking efficiency of the staff

[0003] The optimization method of picking task generation is mostly optimized from two aspects of order batching and path planning. The existing research mainly focuses on the B2C warehouse distribution and picking scenario, and the distance calculation and estimation during path planning are considered to be The travel distance in the picking area, and in the B2B business scenario, the scope of picking operations is not limited to the picking area. Therefore, the use of existing technical solutions will lead to unreasonable picking tasks, which will affect the Picking efficiency

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