11 results about "Product order" patented technology

The invention discloses a product order quantity prediction method and device, a storage medium and equipment. The method comprises the following steps: acquiring an actual order quantity of a first product; based on the actual order quantity of the first product, utilizing a preset gray model to obtain a first prediction value about the future order quantity of the first product; and correcting the first prediction value to obtain a second prediction value about the future order quantity of the first product. By adopting the scheme, the accuracy of product order quantity prediction can be improved.

This application provides a process configuration method, apparatus, device, and storage medium, relating to the field of computer technology, for improving the development efficiency of product trading programs. The method comprises: generating a first scheduling index based on product order information; obtaining a first scheduling rule that matches the first scheduling index from a preset first scheduling rule table; obtaining a second scheduling rule corresponding to each process step based on the call order corresponding to each process step; and executing the process step corresponding to each process node according to the second scheduling rule corresponding to each process step.

A method for managing a product order request includes: obtaining historical data; analyzing the historical data to generate a data set that is associated with a set of parts of a first product; performing preprocessing on the data set to generate a preprocessed data set; generating, based on the preprocessed data set, a model that predicts part failure probability of each part of the set of parts; training the model to generate a trained model that, at least, identifies categories in the preprocessed data set and predicts part failure probability of each part listed in each category prior to a manufacturing process of a second product is initiated; receiving the request from a user; and identifying, using the trained model, a second set of parts that need to be used to manufacture the second product and the best vendor to procure each part of the second set of parts.

The invention relates to an order generation method and device, computer equipment, a storage medium and a product. The method comprises the following steps: displaying a store page of a target store; the store page comprises at least one store commodity of the target store; wherein the store page has an ordering function for store commodities after the target store is claimed by a target management account; and in response to an ordering operation on a target commodity in the at least one store commodity, generating a commodity order. By adopting the method, an efficient ordering guide path can be provided for the user, the complexity that the traditional user scans a code to order an order in a store or skips to other ordering platforms is avoided, the ordering time of the user is greatly shortened, the whole process of grass planting-decision making-transaction is connected in series, and the integration and convenience of a social media platform are further improved.

The present application discloses a method, device, equipment and medium for generating digital coupons based on big data, wherein the method includes: parsing the commodity selection range in the preferential policy generation request; querying all commodity orders that fall into the commodity selection range on the e-commerce platform; obtaining a preferential policy source data set based on at least the commodity SKU code, the original price of the commodity, the commodity order price, the commodity preferential type, the commodity order time and the buyer identification code in the queried commodity order; inputting the preferential policy source data set into a random forest classification model to output the classification result to obtain several preferential policy sub-data sets; generating digital coupons based on the situation of the digital coupons used by the commodity orders corresponding to the preferential policy sub-data sets. The present application is beneficial in that it provides a method, device, equipment and medium for generating digital coupons based on big data that intelligently generates preferential policies based on existing commodity order data.

The invention relates to a product order sequence generation method and device and computer equipment. The method comprises the steps of obtaining product order information of each user, and splitting each piece of product order information into order demand information of each user, an order time type of each user and an order time point of each user; based on the order demand information of each user, identifying product feature information of each product demand type of each user through an order feature analysis strategy, and based on the order time point of each user, the order time type of each user and the product feature information of each product demand type of each user, identifying the product feature information of each product demand type of each user; generating an order generation sequence; and identifying sequence abnormal information of the order generation sequence, and adjusting the sequence abnormal information of the order generation sequence through an order sequence optimization adjustment strategy to obtain a target order generation sequence. By adopting the method, the processing efficiency of all orders in order of a large number of products can be improved.

The invention discloses an intelligent production scheduling method based on arc decomposition. The method comprises the following steps: obtaining order data and production line data; the obtained order data and production line data are utilized, a discretized order space-time network is established according to a minimum comprehensive production cost model, and the order space-time network comprises a plurality of arcs; according to the constraint information, cutting down a plurality of arcs in the order space-time network to obtain a cut-down arc space; solving the production scheduling optimization model based on the reduced arc space to obtain an intelligent production scheduling plan; according to the obtained intelligent production scheduling plan, a production scheduling instruction is sent to the production line, in addition, the invention further discloses an intelligent production scheduling system based on the method, the model is constructed in an arc decomposition mode, production scheduling can be rapidly and accurately conducted on the product orders, and the cost of the production scheduling scheme is greatly reduced.

This application discloses a product order allocation method, apparatus, device, and storage medium, belonging to the field of order management technology. This application obtains a bipartite graph model, where the bipartite graph model is a graph model representing the mapping relationship between an order set and a participant set. The order set is the set of product orders corresponding to users, and the participant set is the set of production plants. The mapping relationship is the correspondence between production plants and order tasks, and the mapping relationship meets task completion conditions, task quantity conditions, and / or pricing conditions. Based on the order tasks and production plants corresponding to the mapping relationship, product orders are allocated. That is, by aggregating the product orders corresponding to users and the production plants, and matching the two aggregated sets, a suitable mapping relationship can be determined in the order set and the participant set. When the mapping relationship meets the corresponding conditions, the corresponding order tasks are allocated, avoiding excessively high production plant costs.

This invention discloses an intelligent order dispatching method and system based on multi-product combination price difference identification, belonging to the field of computer technology. The method includes: acquiring multi-product order data; generating a combination price difference representation vector based on a price difference identification rule base; acquiring a processing party capability profile; performing multi-dimensional matching degree calculation and dynamically adjusting weights; selecting the optimal processing party for order dispatch; and updating the rule base and profile based on feedback data. The system includes corresponding functional modules, supporting price difference identification, capability profile construction, dynamic matching, and online learning. This invention aims to solve the problems of unreasonable order allocation, low efficiency, and reduced revenue caused by the inability of existing order dispatching mechanisms to accurately identify multi-product combination price differences. Through value-driven intelligent matching, it significantly improves order dispatching efficiency, resource utilization, and operational revenue.

To provide a product order fulfillment system for improving the throughput of a storage and retrieval system.SOLUTION: Each level of the multi-level transport system has a corresponding independent asynchronous level transport system that is separate and distinct from the asynchronous level transport system corresponding to each other level of the multi-level transport system. Each independent lift axis of the lifting transport system is configured to independently hold at least one case and is communicably coupled to each asynchronous level transport system to provide exchange of the at least one case between each asynchronous level transport system and each independent lift axis. Each independent lift axis is communicatively coupled to each other independent lift axis of the plurality of lift axes to form a common output of mixed cases to create an ordered sequence of mixed cases according to a predetermined case out ordered sequence.SELECTED DRAWING: Figure 12B

The invention provides an order asynchronous processing method and system, a medium and equipment, and the method comprises the steps: receiving an order request sent by a client, the order request carrying commodity identification information of a commodity requested to be purchased and a purchase quantity; determining the number of tokens in a token bucket corresponding to the commodity identification information; in response to the fact that the token number is not smaller than the purchase number, creating a commodity order corresponding to the order request and setting an order state of the commodity order as an in-order-creation state; carrying out asynchronous processing on the commodity order and the inventory of the commodity; wherein the asynchronous processing of the commodity order comprises the step of carrying out persistent processing on order data of the commodity order, and the processing of the inventory of the commodity comprises the step of carrying out deduction processing on the inventory of the commodity based on the purchase quantity. According to the method and the device, the token bucket is used for smoothly controlling the flow of the order request, the influence on the system caused by excessive instantaneous flow is avoided, and the load pressure of the system can be further relieved by asynchronously processing the order.