Warehouse scheduling method, server and system

Abstract

The invention discloses a warehouse scheduling method, server and system, and relates to the field of warehousing. The method comprises: obtaining, by a warehouse scheduling server, a first prediction value and a second prediction value of the inventory resource quantity of each cargo, wherein the first prediction value is determined based on historical warehouse-out data, and the second prediction value is determined based on a first target metric value; constructing a first inventory influence parameter and a second inventory influence parameter of each cargo and a relational expression between an inventory resource quantity prediction value and a second target metric value; taking the first predicted value and the second predicted value as constraint conditions, and calculating the inventory resource quantity predicted value of each cargo corresponding to the maximum second target metric value; and sending the stock resource quantity prediction value of each cargo to a warehouse management system to instruct the warehouse management system to schedule the cargos in the warehouse. According to the invention, the accuracy of the stock resource quantity prediction result of the cargo is improved, so that the cargo scheduling result is more accurate, and the operation cost is reduced.

Description

technical field [0001] The present disclosure relates to the field of warehousing, and in particular to a warehouse scheduling method, server and system. Background technique [0002] Forecasting technology is the underlying support technology for supply chain optimization, and the quality of forecasting is crucial to subsequent supply chain optimization. In extreme cases, when the inventory drops to zero, replenishment is required. It takes a long time for the supplier to receive the replenishment notice and deliver the goods to the warehouse. During this period, the warehouse is out of stock, which will lead to out-of-stock costs. On the contrary, if the forecast result is too high, it will increase the inventory cost. According to a rough estimate, a 1% increase in forecast accuracy can save several times the operating cost. Therefore, forecasting technology is one of the key technologies in supply chain optimization. [0003] In the related technology, single-stage co...

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Problems solved by technology

[0003] In the related technology, single-stage commodity forecasting is adopted, which is based on the forecast under the original assumptions or data conditions. From the perspective of forecast implementation, missing data features or poor data quality, etc., cause problems such as islands of information in the original model, making the forecast The result is inaccurate, which leads to unreasonable warehouse scheduling, and the operating cost is stated

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