Wave planning method using roadway concentration and minimum set coverage

Abstract

The invention discloses a wave planning method using roadway concentration and minimum set coverage. The method comprises the following steps: setting roadways in wave as a set, and setting commodities in stock on the roadways as set members of the roadways; determining the roadways which must pass through, and arranging the goods belonging to the roadways in the roadways for picking; removing the selected commodity stock from the to-be-picked set S, judging whether a roadway which must be passed exists or not, if yes, turning to the previous step, and if not, turning to the next step; calculating the number of commodities of each roadway on the to-be-picked set S, selecting the roadway with the maximum number of commodities, and arranging the commodities in the roadway with the maximum number of commodities for picking; removing the selected commodities from the to-be-sorted set S, judging whether the to-be-sorted set S has commodities or not, if yes, turning to the previous step, and if not, turning to the next step; and outputting the wave order. According to the invention, the walking distance of order picking is indirectly optimized by optimizing the number of the roadways through which order picking needs to pass, so that the problem that the walking distance of order picking cannot be optimized during order picking is solved.

Description

technical field [0001] The invention belongs to the technical field of warehouse picking, and in particular relates to a wave planning method using roadway concentration and minimum set coverage. Background technique [0002] In e-commerce warehousing, a large amount of order information will flow in real time, and the warehouse system will pick goods according to the inventory information and order requirements. There are many products stored in the e-commerce warehouse, and the orders are relatively small, which makes it very difficult to pick a single order. In this situation, the order demand of a wave is aggregated first. The goods of a wave are distributed in various areas of the warehouse, and each area will form a task. The picking workers in this area will be responsible for picking the goods corresponding to this task. These products that have been selected by different regions will be combined together and sorted into a single wave of product sets, and the product...

AI Technical Summary

Problems solved by technology

[0003] At present, most of the sub-waves accumulate a certain amount of orders or orders within a period of time to form a wave. The downstream picking directly traverses each area to query the maximum number of commodities that the area can bear for this wave, and then allocates until All commodity demands in a wave are allocated, and to plan which warehouse location each commodity should pick up, generally use package similarity to cluster packages or use operations research to specifically install the inventory of each commodity, but currently there is no An effective method for selecting the inventory of each product to improve the picking efficiency in the generalized wave is generally optimized by using some solidified rules or clustering methods. The focus of existing technologies is on the inventory of the product dimension. Decision-making, to decide which location to pick up inventory for each order and each product, often takes a lot of time to calculate, or oversimplifies the problem, making the picking efficiency low. In the approximate wave, use fixed rules or It is a clustering method to select the final inventory of each product, and the picking efficiency is not high

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