62 results about "Inventory optimization" patented technology

In one embodiment, optimizing inventory for a supply chain includes generating an inventory plan for the supply chains. Execution of a supply chain plan associated with the inventory plan is initiated at the supply chain. The supply chain is monitored to generate metric values. A watchpoint triggered by a metric value is detected, and a cause of the triggered watchpoint is identified using a causal tree. The inventory plan is adjusted in response to the detected triggered watchpoint and in accordance with the identified cause, and the supply chain plan is adjusted in accordance with the adjusted inventory plan. Execution of the adjusted supply chain plan is initiated, and new metric values are measured to determine performance. The performance is evaluated, and the causal tree is updated in response to the evaluation.

System(s) and method(s) to provide inventory optimization in a multi-echelon supply chain network are disclosed. An input data comprising one or more product supply parameters along with an uncertainty factor associated with the product supply parameters are received through a configurable user interface. The input data is used to create a multi-echelon supply chain network. Supplier nodes are selected based on optimizing parameters and are allocated with respect to demand nodes. A lead time demand and a safety stock parameter are calculated. An optimal inventory plan is generated for each supply chain member associated with the supply chain network along with the safety stock parameter by minimizing the uncertainty factor thereby providing the inventory optimization. The optimal inventory plan is displayed in one or more parameters over the configurable user interface.

The invention provides a steelmaking-continuous casting-hot rolling integrated scheduling method and system. The method comprises the steps of S1, performing initialization to obtain a steelmaking-continuous casting scheduling plan; S2, obtaining a hot rolling scheduling plan according to the current steelmaking-continuous casting scheduling plan as well as a working order demand, a production line model, a current production rhythm, a rolling unit length constraint, and a rolling unit internal adjacent plate blank width, thickness and hardness jump constraint; S3, determining whether an inventory change situation meets a preset inventory optimization plan or not according to the current steelmaking-continuous casting scheduling plan and the hot rolling scheduling plan, and if the preset rule is met, entering the next step, otherwise, adjusting current parameters related to inventory optimization and returning to the step S1; S4, obtaining overall heat supply rate data according to the current steelmaking-continuous casting scheduling plan and the hot rolling scheduling plan; S5, judging whether an integrated scheduling stop condition is met or not, and if the stop condition is met, performing the scheduling plan, otherwise, performing the next step; and S6, performing re-optimization to generate the steelmaking-continuous casting scheduling plan, and returning to the step S2.

The invention relates to a supply chain inventory optimization method for lightweight information sharing. The method comprises the following steps: (1) acquiring order and replenishment information of wholesalers or retail dealers; (2) inquiring inventory data of distributors according to the order and replenishment information; (3) predicting order points and economic order quantity of the distributors in lead time of order; (4) judging whether the replenishment information is generated or not and generating a warning notification; (5) sending out an order application to upstream enterprise according to the replenishment information; (6) generating a centralized distribution scheme according to the shortage cost, the discount cost and the transportation cost of the wholesalers and the retail dealers, and sending delivery information to the wholesalers or the retail dealers; (7) updating an inventory database of the distributors after the distributors receive the distribution information of the upstream enterprise. According to the supply chain inventory optimization method disclosed by the invention, the optimal centralized distribution scheme for enabling the total cost of a supply chain to be lowest can be made when order requirements of the retail dealers or the wholesalers arrive, and the double marginal effect of the supply chain is eliminated.

An inventory optimization system is disclosed. The system comprises of an inventory interface configured to receive inventory policy criteria representing possible conditions of a plurality of inventory policies by which an inventory could be managed. An optimization engine is provided to generate the plurality of inventory policies based on the inventory policy criteria with each inventory policy having an assumed future demand model. The optimization engine is also configured to use a simulation engine to simulate how each inventory policy would perform (i.e. a cost to run the inventory policy) under different estimated demand. The optimization engine is configured to rank the plurality of inventory policies based on their performance under the simulations.

The invention discloses a cloud logistics platform and a construction method, and belongs to the technical field of cloud logistics. The invention provides the cloud logistics platform and the construction method of the logistics platform, and the logistics platform comprises a platform system architecture, a big data processing center and a user layer. The construction method of the logistics platform comprises the following steps: S1, constructing a logistics task; S2, establishing a service resource library; S3, constructing a logistics task and cloud logistics service resource combinationmodel; S4, performing big data mining and logistics demand prediction; S5, performing logistics storage planning and joint inventory optimization; and S6, performing logistics transportation and terminal distribution optimization. Through the cloud logistics platform, the relationship between the logistics resource provider and the logistics demand can be well communicated. Sharing and on-demand using of logistics resources, logistics capacity and logistics knowledge are achieved, selection, communication and service matching are provided for enterprises and individuals with logistics demandsthrough a public cloud logistics service platform, and logistics services which are obtained by users at any time, serve on demand, safe, reliable, high in quality and low in price are achieved.

The present invention provides an inventory optimization management information model based on a capacity supply chain. A construction method for the model involves a client demand information collection module, a client information processing module, a production plan scheduling board visual module and an inventory classification delivery module. The method comprises the specific steps of: establishing a client demand information unit; inputting client information for performing a demand classification process; summarizing data to a data exchange center for later use; establishing a corresponding client order task; releasing a production plan and organizing production by a visual display screen; performing classification on finished products for later delivery; monitoring a delivery period to ensure delivery to a user according to the time required by the user; and finishing order delivery, returning detailed data of the order delivery to the data exchange center for archiving, and eliminating the corresponding task. According to various factors such as a user ordering habit and the like, an inventory coefficient can be intelligently calculated, a user ordering demand can be predicted, and inventory can be reasonably prepared, so that on the premise of ensuring supply, finished product inventory can be reduced, and occupied capital is reduced.

The invention discloses a supply chain inventory optimization method, apparatus and device, and a storage medium. The method comprises the steps of obtaining a first replenishment strategy of a target commodity; comparing a first replenishment effect parameter of the first replenishment strategy with a preset evaluation parameter; if the first replenishment effect parameter is smaller than the preset evaluation parameter, optimizing the first replenishment strategy to obtain a second replenishment strategy; and generating an inventory suggestion of the target commodity according to the second replenishment strategy, wherein the inventory suggestion is used for indicating replenishment time and replenishment amount of the target commodity. The first replenishment effect parameter is compared with the preset evaluation parameter, the first replenishment strategy is optimized to obtain the second replenishment strategy of which the replenishment effect parameter is greater than or equal to the preset evaluation parameter, and the inventory suggestion about the target commodity is generated according to the second replenishment strategy, so that the inventory and the cost brought by the inventory are effectively reduced; and the inventory efficiency capable of meeting the service level is improved, and the labor cost and the time cost of inventory optimization are saved.

The invention provides a retail industry inventory optimization analysis method. The retail industry inventory optimization analysis method comprises the following steps of step S1, determining a safety inventory according to a customer demand, an ordering advance period and a customer service level; step S2, calculating an ordering point according to the safety stock and the average daily demandin the ordering advance period; step S3, predicting the future sales volume through the historical sales volume data by using an autoregression model so that the order quantity is determined; and stepS4, for multi-commodity sales volume prediction in which a plurality of single-commodity multi-dimensional relationships are interleaved together, improving prediction accuracy through multi-level prediction adjustment. The inventory cost can be saved, and the customer service level is improved.

The invention discloses a dynamic inventory optimization method which mainly comprises the following steps: (1) constructing a dynamic inventory optimization model which comprises a static model and a dynamic model; (2) acquiring input data, sales volume data, warehouse data, order data, purchase data and cargo data; (3) importing the data and information into an inventory optimization model to form a corresponding transfer function or constraint condition; and (4) constructing a model algorithm, and solving the optimal stock quantity of the goods and the corresponding optimal rental area of the warehouse in the static model and the dynamic model. The dynamic inventory optimization model of the standard food materials is constructed in combination with actual market requirements and enterprise operation conditions, and the optimal goods inventory and the optimal warehouse scale are determined from static and dynamic angles, so that the inventory management problem in the standardized food material supply process is solved, the turnover speed of goods in a warehouse is increased. And the fund turnover efficiency of a company is improved.

The invention discloses an intelligent supply chain inventory transfer optimization and transaction early warning system. The system comprises an initial inventory optimization subsystem and an inventory transaction early warning and strategy updating subsystem. The initial inventory optimization subsystem comprises an upstream replenishment prediction module, a downstream demand learning module and an inventory optimization module. The upstream replenishment prediction module predicts the replenishment condition of an upstream supplier by using historical warehousing data, and the downstream demand learning module learns and predicts the demand of a downstream consumer by using historical order data; the upstream replenishment predicted quantity and the downstream demand predicted quantity are imported into an inventory optimization module, and an initial inventory optimization scheme is output. The inventory transaction early warning and strategy updating subsystem comprises an inventory transaction identification module and a time early warning and strategy updating module. The inventory transaction identification module identifies the updated inventory information to judge whether the inventory information deviates from the expectation or not, and carries out early warning and allocation plan updating on the time when the inventory reaches the warning line through the time early warning and strategy updating module when the inventory information deviates from the expectation.

The invention provides an inventory optimization control system and method suitable for automobile after-sales accessories, and the method comprises the steps: obtaining data of dealers, suppliers andaccessories to acquire the vehicle retention data and accessory sales summary data of different ages; obtaining engineering information of the accessory; establishing a prediction management model for the accessory sales through a parallel computing method according to the vehicle ownership data of sub-vehicles, the accessory sales summary data and the engineering information of the accessories,and predicting the accessory sales; making a preset strategy for the specified accessories, and predicting sales data of each accessory according to the prediction management model to calculate an accessory inventory strategy; calculating an order strategy for each logistics node in a timed task mode according to the accessory inventory strategy; according to the invention, automatic demand prediction and prediction model parameter optimization capabilities of after-sales accessories are realized, and an after-sales department is helped to save a large amount of follow-up processing time of invalid information.

The invention relates to a retail field supply chain inventory optimization method based on sales volume prediction. The content of the invention mainly comprises (1) a commodity sales volume accurate prediction method based on polymorphic feature fusion; and (2) a supply chain inventory optimization method under logistics constraint based on commodity activeness classification. On the basis of the method, the polymorphic feature data of the commodities are extracted and fused, and the supply chain inventory optimization model is constructed by performing activeness classification according to the predicted sales volume of the commodities, so that the sales volume prediction-based retail field supply chain inventory optimization method is realized, and fund turnover is accelerated.

A method and apparatus for campaign and inventory optimization have been disclosed. In one version inventory optimization occurs by determining which products to show when.