An intelligent ordering system for a fresh food store

Abstract

The invention discloses a intelligent ordering system of a fresh food store comprising: a commodity sales volume prediction module which is used for determining a discount promotion time point and predicting the sales volume of each commodity before discount promotion; an order module which is used for determining the actual order quantity of each commodity; And a promotion module which is used for acquiring the time point of discount promotion and the discount number of the commodities after the time point of discount promotion from the commodity sales prediction module. According to the system, the recommended value of the order quantity of each commodity every day is provided for the store, so that the order is simpler and more intelligent; The commodities are reasonably and objectivelyordered; The method has the advantages that the richness of commodities capable of being sold in the fresh store is planned comprehensively, the problem that the store loses or is insufficient in supply due to too much or too little commodities can be solved to the maximum extent, a set of store promotion scheme can be provided, the consumption experience of store customers is improved, and the customer purchase experience of the fresh market store is improved.

Description

technical field [0001] The invention relates to the technical fields of data mining and operations research, in particular to an intelligent ordering system for fresh food stores. Background technique [0002] In some fresh food stores, the requirements for the freshness of the goods are very high. The traditional ordering method in these markets or stores is to order according to the experience of the clerk or the store manager, which has a lot of personal subjectivity and requires high store management experience of the orderer. This traditional ordering method often causes losses such as deterioration of goods that cannot be sold on the same day due to excessive purchases, or insufficient supply of goods due to insufficient purchases. Too much or too little purchase will be detrimental to the operation of the enterprise, and it will also affect the customer's consumption experience. Contents of the invention [0003] Aiming at the problems existing in the prior art, t...

AI Technical Summary

Problems solved by technology

[0003] Aiming at the problems existing in the prior art, the present invention proposes an intelligent ordering system for fresh food stores, which provides fresh food stores with the ordering value of each product of the day through optimization methods such as data mining technology and operations research, and solves the problem of ordering fresh food stores. Unreasonable problems minimize the loss rate of products, increase the variety of products on sale, and obtain more profits for stores

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