64 results about "Inventory optimization" patented technology

The disclosure relates to analyzing and visualizing flows in a supply chain context for the purpose of inventory optimization. Embodiments disclosed include a method of analyzing a process flow in a supply chain context, the method comprising: inputting (3402) a first set of data to an application residing on a processor, relating to products, locations and supply routes connecting the different locations in the supply chain; the application generating (3403) from the first set of data an input data array; inputting (3404) a second set of data relating to measured and forecast flows of products through the supply chain over a defined time period; the application calculating (3405) from the data a series of measures of operation of the supply chain; and, based on one or more of the measures being outside a predefined range, the application generating (3406) an output indicating recommendations for adjusting operation of the supply chain.

Embodiments of the invention disclose an output method and apparatus, and an electronic device, and relate to an automated logistics technology. The output efficiency can be effectively improved. Theoutput method comprises the steps of receiving a to-be-output order in an output process; performing combination processing on the to-be-output order and an order which is being output currently to obtain a combined order; according to stored cargo attributes in the combined order, obtaining cargo shelf information matched with the stored cargo attributes; and according to a preset cargo shelf information output policy, matching the obtained cargo shelf information to obtain target cargo shelf information. The output method and apparatus is suitable for output and inventory optimization.

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.

A method and system for optimizing cutting of various materials. In some embodiments, an algorithm optimizes cutting by grouping items to be cut, wherein a plurality of cutting-stock pieces are grouped together and aligned such that a single cut simultaneously cuts items from all of the pieces. Some embodiments optimize a combination of reduced labor cost, reduced materials cost (e.g., reducing scrap), and / or reduced time needed to obtain an inventory of pieces cut to specified lengths and shapes (checking the various permutations). Overall optimization of labor and material is achieved by a combination of fewer cuts and reduced waste. Some embodiments include a computer-readable medium having instructions executed by a computer that optimizes placement of cuts to obtain cut-part items, and optionally controls a saw, laser, water-jet cutter or the like. In some embodiments, a human operator making the cuts is instructed by the computer to achieve the optimization.

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 disclosure relates generally to methods and apparatus to optimize a supply plan through a hybrid meta-heuristic approach based on genetic algorithms to optimize inventory and generate a supply plan. The apparatuses include a supply chain planner that interacts with the processes of a supply chain network. To provide a complete optimization for the type of platform being deployed in theater a heuristic algorithm is devised to decompose the supply plan problem into a production center schedule and an asset routing problem, which will be tackled one after the other. The decomposed supply plan problem is solved with different heuristic algorithms. Namely, genetic algorithms are used to optimize the supply plans based on ever changing set of operational demands from in theater and the priority of those demands to the assigned depots, while efficient constructive heuristics are used to deal with footprint and timing constraints.

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.

A method and system for optimizing cutting of various materials. In some embodiments, an algorithm optimizes cutting by grouping items to be cut, wherein a plurality of cutting-stock pieces are grouped together and aligned such that a single cut simultaneously cuts items from all of the pieces. Some embodiments optimize a combination of reduced labor cost, reduced materials cost (e.g., reducing scrap), and / or reduced time needed to obtain an inventory of pieces cut to specified lengths and shapes (checking the various permutations). Overall optimization of labor and material is achieved by a combination of fewer cuts and reduced waste. Some embodiments include a computer-readable medium having instructions executed by a computer that optimizes placement of cuts to obtain cut-part items, and optionally controls a saw, laser, water-jet cutter or the like. In some embodiments, a human operator making the cuts is instructed by the computer to achieve the optimization.

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 invention discloses a distributed logistics inventory optimization method based on a cloud calculation environment. The method includes the steps of S1, building the algebraic model and constraintcondition function of an evaluation function f(U); S2, calculating the value of each component, and building the optimal equation matrix HM of harmony inventory; S3, using probability P(Xi) to replace harmony memory considering rate HMCR, and generating a new solution vector according to a harmony searching algorithm; S4, calculating the target function value f(Ub) of the new solution vector according to the evaluation function f(U), comparing the target function value f(Ub) of the new solution vector with the target function value f(Ub) of an original solution vector, and updating the inventory; S5, repeating the steps from S2 to S4, stopping until preset maximum iteration times are reached, and outputting optimal solution. By the method which is fast in response and optimization speed and high in multi-target optimization calculation efficiency, distributed logistics inventory pre-warning and cost optimization under the cloud calculation environment are achieved, and the dynamic management of the distributed logistics inventory is achieved.

The invention relates to a computer warehouse management system, which mainly comprises a central processing system and a data acquisition terminal exchanging data with the central processing system, wherein the data acquisition terminal acquires warehouse in / out data of various goods, which is sent into the central processing system; the central processing system counts, analyzes and stores the warehouse in / out data; and the central processing system is provided with a real-time inventory database and an inventory optimization database, as well as a data statistics unit, a data comparing-analyzing unit, a data storing-outputting unit, a manual input device and a central control unit. The system not only can realize the acquisition and statistics of warehouse data but also can optimize and control the inventory mode, inventory level and inventory time of the goods according to the management states of enterprises, alarms for optimization problems, and is favorable for raising the operating management level of the enterprises on the whole.

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 provides a method and a system for optimizing inventory. The method comprises the following steps: receiving material data related to inventory; screening the received material data, and getting a potential material requirement planning MRP management bill of materials (BOM); carrying out regional division on a to-be-evaluated material in the MRP management BOM according to at least one of inventory importance, demand characteristic and value; and setting the mode of storage of the to-be-evaluated material to automatic replenishment or setting the mode of storage of the to-be-evaluated material to zero-inventory on-demand procurement according to the result of regional division, and predicting the quantity and time of demand. According to the method, the material data is screened, regional division is carried out on the to-be-evaluated material in the MRP management BOM, and the mode of storage of the to-be-evaluated material is set to automatic replenishment or zero-inventory on-demand procurement according to the result of regional division. Thus, inventory is reduced, the turnover rate of inventory is increased, and inventory optimization is realized.

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 relates to an enterprise inventory optimization management system, which mainly comprises a central computer system, a plurality of data gathering terminals and a plurality of monitoring displays, wherein the central computer system and the data gathering terminals are connected through signals, the data gathering terminals gather database-in and database-out data which feed various goods to the central computer system, the central computer system is used to numerate, analyze and store the database-in and database-out data, and is provided with a real time inventory database and an inventory optimization database. The enterprise inventory optimization management system can achieve the gathering and the numerating of inventory data, and can optimize and control inventory mode, inventory quantity and inventory time of goods according to an enterprise operation state, generates warning signals through a warning unit when optimization problems appear, and alarms through a display and / or a warning device, and the warning signals are simultaneously fed to a monitoring display to display. The enterprise inventory optimization management system has reasonable structure, which is beneficial for improving enterprise operation management level from integral body.

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 relates to a remote computer storehouse management system which mainly comprises a central processing system and a remote data collection terminal made data exchange with the central processing system. The remote data collection terminal is provided with a wireless transmitting and receiving module, the central processing system is provided with a supporting wireless transmitting and receiving module, stock-in / out data is statisticized, analyzed and stored, the central processing system is provided with a real-time inventory database, an inventory optimization database, a data statistics unit, a data comparison and analysis unit, a data storage and output unit, a manual input device and a central control unit. The system can not only realize the collection and the statistics of the inventory data, but also can optimize and control the inventory mode, the inventory level and the inventory time of the goods according to the operation state of the enterprise, alarms when the optimization problem appears, and contributes to improving the operation management level of the enterprise on the whole.

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 provides an ethanol inventory replenishment strategy based on a multi-objective particle swarm optimization algorithm, which aims to solve the problem that the ethanol inventory is difficult to optimize and determine, realize the reasonable planning of the ethanol inventory replenishment quantity and reduce the total cost of the ethanol inventory. The ethanol inventory replenishmentstrategy comprises the following steps of establishing a storage cost model and a purchase cost model to obtain a relation between cost and replenishment batches, and starting a replenishment strategyinventory margin and delivery time; optimizing a storage cost model and a purchase cost model by using a multi-objective particle swarm optimization algorithm; obtaining a fixed replenishment batch during each replenishment in a single period, and starting the optimal set values of the inventory allowance and the delivery time of the replenishment strategy, so that the ethanol inventory is kept at a reasonable level, the inventory optimization control is promoted, and the stable operation of the industrial process is ensured.

The invention discloses a service information publishing method and system. The service information publishing method comprises the steps that service information to be distributed and directed goals corresponding to the service information to be distributed are selected, the demand quantity of the service information to be distributed is set, and the quantity of the current remaining inventory of the directed goals is queried; if the demand quantity is larger than the quantity of the current remaining inventory of the directed goals, pre-distribution is conducted on the service information to be distributed, and inventory optimization is conducted on the quantity of the current remaining inventory of a directed goal set through a preset optimization module; the optimized quantity of the inventory of the directed goals is obtained; if the optimized quantity of the inventory of the directed goals is larger than the demand quantity, the service information is ordered to the be published to the directed goals.

The invention discloses a pharmacy management system. The pharmacy management system comprises an on-line service platform, a personal management module, a doctor management module and a pharmacy management module, wherein the online service platform includes a registration management unit, a data storage unit, an order generation unit, a transaction settlement unit, and a data statistics unit; the personal management module includes an appointment registration unit, an information inquiry unit, and an order payment unit; the doctor management module includes a patient information extraction unit, an inquiry unit and a diagnosis unit; the pharmacy management module includes an institutional prescription management unit, an institutional prescription review unit, a delivery management unit,and an inventory optimization unit; the data statistics unit counts the proportion of various types of drugs in the completed transaction order; and the inventory optimization unit receives the statistical results of the data statistics unit and adjusts the stored drugs according to the proportion. The pharmacy management system can improve the consultation efficiency of the patient and rationalize the drug inventory in the pharmacy.

Computer program products, methods, systems, apparatus, and computing entities for carton inventory optimization are provided. An example method comprises: (a) receiving historical shipping data corresponding to a time period, the historical shipping data comprising items that were shipped during the time period and their respective dimensions; (b) associating a rank to each of a plurality of carton sizes for each item; (c) associating a highest ranked carton size for each item at least in part on step (b); and (d) determining whether a desired level of optimization has been reached. Another example method may further comprise: (e) after determining that the desired level of optimization has not been reached, identifying at least one carton size; and (f) re-associating items that were associated with the at least one identified carton size to the next highest ranked carton size for each item.

The invention discloses an online retailer product inventory decision-making method and system based on demand prediction, and belongs to the field of big data prediction and operation optimization. Comprising the steps of predicting demands of each ordering period in a product ordering period of an online retailer; converting the predicted demand of the product in each order period into a fuzzy demand by using a triangular fuzzy number; substituting the fuzzy demand of the product in each order period into the inventory optimization decision model and solving to obtain the optimal order quantity of the product in each order period; according to the method, the situation that prediction is not always accurate is considered, and demand prediction and an inventory optimization model are fused together through fuzzy demands. The product demand of an online retailer is predicted by using big data and a big data analysis technology, a prediction result is converted into a fuzzy demand based on a triangular fuzzy demand, and the fuzzy demand is substituted into a dynamic batch model to solve the problem of the multi-cycle optimal ordering number of products. And technical support can be provided for enterprises to perform inventory optimization management by applying big data.

The invention takes a KNN algorithm as the core to realize temporal classification of mass inventory materials in a material storage process of an electric power company according to a power grid material in-stock situation and through dimensions of prefectural and municipal unit, material type, movement type, factory type, warehousing batch number, storage time, unit price, aggregate amount, current date and material warehousing data. Through the classification method provided by the invention, characteristic data classification of electric power material in-stock inventory is realized, material storage time and regions are divided, and normality, expiration and time-limit-exceeding identification of inventory time is effectively achieved.

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.