Drug replenishment method and device, electronic equipment and storage medium

Abstract

The invention relates to the field of data processing, in particular to a medicine replenishment method and device, electronic equipment and a storage medium. The method comprises the steps that through real-time analysis of current order data and current medicine data, which medicine items need to be replenished and the replenishment quantity needed by each medicine item can be accurately identified, the problem of excessive inventory or inventory shortage is avoided, and the inventory turnover rate is improved. Meanwhile, when replenishment medicine items are determined, the batch number corresponding to each replenishment medicine item can be determined at the same time, due to the fact that different batch numbers possibly represent different production dates, validity periods or production batches, important significance is achieved for guaranteeing the medicine quality and the patient safety, and through strict batch number management, the number of the replenishment medicine items is greatly reduced. The risk of using expired or unqualified drugs can be effectively avoided, the whole process is an automatic and intelligent replenishment process, the labor cost in the drug replenishment process is reduced, and meanwhile the possibility of human errors in the drug replenishment project is reduced.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a drug replenishment method, device, electronic device and storage medium. Background Art

[0002] The process of drug replenishment generally involves formulating a replenishment plan that includes the drug items and quantities to be replenished based on inventory conditions and sales forecasts, then contacting the selected supplier to place an accurate purchase order, and placing the replenished drugs in the corresponding storage locations after they arrive.

[0003] With the development of technology, existing replenishment plans are generally generated through electronic devices such as mobile phones. Electronic devices obtain sales data and analyze the sales of various types of drugs, including sales volume, sales speed, etc., and determine the types and quantities of drugs that need to be replenished through historical sales data and market demand forecasts. Replenishment plans are formulated based on current inventory conditions and sales forecasts. However, after the replenished drugs arrive, replenishment personnel are still required to store the arrived replenished drugs, which requires a lot of labor costs. Summary of the invention

[0004] In order to reduce the labor cost in the process of drug replenishment, the present application provides a drug replenishment method, device, electronic device and storage medium.

[0005] In the first aspect, the present application provides a method for replenishing medicines, which adopts the following technical solution: A drug replenishment method, comprising: Obtaining current order data and current drug data corresponding to the current cycle, wherein the current order data includes order sub-data corresponding to each order in the current cycle, wherein the order sub-data includes drug items and the shipment volume corresponding to each drug item, and the current drug data includes the quantity, batch number, and storage location corresponding to each drug item; Based on the current order data and the current drug data, determine the replenishment drug items in the future period and the quantity and batch number corresponding to each of the replenishment drug items; Determine the storage location for each replenishment drug item; Generate a replenishment plan based on the replenishment drug items and the corresponding drug quantity, storage location and batch number; Based on the replenishment plan, a replenishment task corresponding to each replenishment drug quality is generated, and the replenishment task is executed.

[0006] By adopting the above technical solution, by real-time analysis of current order data (including drug items and shipments under each order) and current drug data (quantity, batch number, storage location), it is possible to accurately identify which drug items need to be replenished and the replenishment quantity required for each, avoiding the problem of excessive inventory or inventory shortage, thereby improving inventory turnover. The replenishment drug items, quantities and batch numbers are determined through an automated process, and a replenishment plan is immediately generated, which is then quickly converted into a replenishment task and executed, significantly reducing the waiting time from order processing to actual replenishment, and improving overall operational efficiency. At the same time, when determining the replenishment drug items, the batch number corresponding to each replenishment drug item will be determined at the same time, because different batch numbers may represent different production dates, expiration dates or production batches, which is of great significance for ensuring drug quality and patient safety. Through strict batch number management, the risk of using expired or unqualified drugs can be effectively avoided. The entire process is an automated and intelligent replenishment process, which reduces the labor cost in the drug replenishment process and reduces the possibility of human errors in the drug replenishment project.

[0007] In a possible implementation, based on the current order data and the current drug data, determining the replenishment drug items in a future period and the quantity corresponding to each replenishment drug item includes: Acquire historical order data, wherein the historical order data includes order data corresponding to each historical period; Based on the historical order data and the current order data, predict future order sub-data corresponding to a future period; Based on the current order data, the future order sub-data and the current drug data, the replenishment drug items in the future period and the quantity corresponding to each replenishment drug item are determined.

[0008] By adopting the above technical solutions, seasonal, cyclical or trend changes in drug demand can be identified by acquiring and analyzing historical order data. Combining current order data with predicted future order sub-data can more comprehensively evaluate the relationship between current inventory status and future demand. Through accurate prediction and timely replenishment, the system can effectively reduce sales losses and customer dissatisfaction caused by out-of-stock, while avoiding capital occupation and increased storage costs caused by excess inventory, which helps to improve the overall operational efficiency and profitability of the enterprise.

[0009] In a possible implementation, based on the historical order data and the current order data, future order sub-data corresponding to a future period is predicted, wherein the prediction process of the future order sub-data corresponding to each drug item in the future period includes: Establishing probability curves corresponding to each historical period, wherein the probability curves are used to characterize the probability density distribution of the shipment volume of pharmaceutical items; Based on the probability curves corresponding to each historical period and the current order data, predict the safe quantity of the drug items in the future period; Based on the safety quantity corresponding to the pharmaceutical item and the current order data, the future order sub-data corresponding to the pharmaceutical item is determined.

[0010] By adopting the above technical solution and establishing the probability curve corresponding to each historical period, the solution can capture the historical distribution law and trend of drug item shipments. The prediction method based on big data is more comprehensive and accurate than relying solely on current order data. When predicting the safe quantity of drug items in future cycles, it not only considers the current order data, but also combines the probability distribution of historical shipments, which helps to more accurately assess future demand, thereby avoiding over-replenishment or under-replenishment. At the same time, based on the predicted safe quantity and current order data, the replenishment quantity of each drug item can be flexibly determined, thereby ensuring that the replenishment plan can not only meet current demand, but also reserve space for possible future growth.

[0011] In a possible implementation, the historical order data includes the general replenishment quantity, emergency replenishment quantity, and replenishment time of each drug item corresponding to each historical period, and the prediction of the safe quantity corresponding to the drug item in the future period based on the probability curve corresponding to each historical period and the current order data includes: Based on the probability curves corresponding to each historical period, calculate the historical replenishment volume variance and historical replenishment volume mean; Divide each historical period into at least two historical sub-periods, and obtain historical sub-orders corresponding to each historical sub-period, wherein the historical sub-orders include the historical sub-shipment volume corresponding to each drug item; Based on the historical order data, determine the corresponding historical sub-replenishment quantity of each drug item in each historical sub-period; Based on the historical sub-orders corresponding to each historical sub-period and the historical sub-replenishment quantities corresponding to each drug item, a first reference quantity of each drug item corresponding to each historical period is calculated; Calculate the average of the first reference amount of each drug item corresponding to each historical period to obtain the second reference amount corresponding to each drug item; Determine the confidence level corresponding to the general future replenishment quantity in the future period based on the second reference quantity corresponding to each drug item; Determine a future general replenishment confidence interval corresponding to a future period based on the confidence level, the historical general replenishment quantity corresponding to each of the historical periods, the historical replenishment quantity variance, and the historical replenishment quantity mean; Determine the future general replenishment quantity corresponding to the future general replenishment confidence interval; Determine the future emergency replenishment quantity corresponding to the future period based on the historical general replenishment quantity and the historical emergency replenishment quantity corresponding to each historical period; Determine the expected shipment volume for the current period based on the current order data and the probability curves corresponding to each historical period; Based on the estimated shipment volume, the future general replenishment volume, and the future emergency replenishment volume, determine the safe quantity corresponding to the drug item in the future period.

[0012] By adopting the above technical solution, not only the general replenishment and emergency replenishment of the historical cycle are considered, but also the historical sub-cycles and sub-orders are further subdivided, so that the fluctuations and trends of the shipments of pharmaceutical items can be captured more carefully. By calculating the variance, mean, first reference quantity and second reference quantity of the historical replenishment, the principles of statistics are used to quantify the characteristics of historical data. At the same time, the probability density distribution of the shipment volume is characterized by the probability curve, so that the prediction results are more in line with the actual situation, the confidence interval of the future general replenishment is determined, and the future general replenishment volume is selected based on the interval, which increases the reliability and robustness of the prediction results. At the same time, the scheme not only predicts the future general replenishment volume, but also considers the determination of the emergency replenishment volume. The dual replenishment strategy helps enterprises better balance inventory levels and respond to sudden demands. Under normal circumstances, the general replenishment volume can meet most of the demand; when the demand surges, the emergency replenishment volume can be used as a supplement to ensure the stability of the supply chain. When the expected shipment volume is high, the replenishment volume can be increased in advance to avoid out-of-stock; when the expected shipment volume is low, the replenishment volume can be reduced to reduce inventory costs. This flexibility helps enterprises better adapt to market changes.

[0013] In a possible implementation, based on the historical general replenishment quantities and the historical emergency replenishment quantities corresponding to the respective historical periods, determining the future emergency replenishment quantities corresponding to the future period includes: The correlation between the general replenishment quantity and the emergency replenishment quantity is determined based on Formula 1, where Formula 1 is: , is the correlation between general replenishment quantity and emergency replenishment quantity, n is the number of historical cycles, is the historical general replenishment quantity corresponding to the i-th historical period, is the average value of the historical general replenishment quantity corresponding to multiple historical periods, is the historical emergency replenishment quantity corresponding to the i-th historical period, is the average value of the historical emergency replenishment quantity corresponding to each historical period, is a constant; Determining whether the degree of association is greater than a degree of association threshold; If the correlation is greater than the correlation threshold, the first fitting parameter and the second fitting parameter are determined based on the historical order data corresponding to each historical period, and the future emergency replenishment quantity corresponding to the future period is determined based on the correlation and Formula 2, where Formula 2 is: ,in, is the future emergency replenishment quantity corresponding to the future cycle, is the first fitting parameter, is the correlation between general replenishment quantity and emergency replenishment quantity, is the general emergency replenishment quantity corresponding to the future cycle, is the second fitting parameter; If the correlation is not greater than the correlation threshold, each historical order data is analyzed to obtain the contribution coefficient between the historical average of general replenishment quantities and the historical average of emergency replenishment quantities, and the future emergency replenishment quantity corresponding to the future period is determined based on Formula 3, where Formula 3 is: ,in, is the future emergency replenishment quantity corresponding to the future cycle, is the contribution coefficient, To fine-tune the forecast value of emergency replenishment quantity based on general replenishment quantity and correlation.

[0014] By adopting the above technical solution, by comprehensively considering the relationship between the historical general replenishment volume and the historical emergency replenishment volume, and their impact on future replenishment demand, two different forecasting strategies are adopted: When the correlation is high: using historical data, the first fitting parameter and the second fitting parameter are determined by formula, and the future emergency replenishment volume is directly calculated based on these parameters and the current general replenishment volume forecast value, that is, by making full use of the regularity and trend of historical data, the forecast result is more accurate and reliable. When the correlation is low: it does not directly rely on the linear relationship between the general replenishment volume and the emergency replenishment volume, but by analyzing each historical order data, the contribution coefficient of the average general replenishment volume to the average emergency replenishment volume is obtained, which can capture more nonlinear and complex correlations, thereby improving the accuracy of the forecast.

[0015] In a possible implementation, determining the storage location corresponding to each replenishment drug item includes: Obtaining current storage location information corresponding to each of the replenished drug items, wherein the current storage location information includes a storage location and a storage location size; Filtering out target drug items that meet preset conditions from multiple replenishment drug items, and determining the replenishment drug items other than the target drug items as remaining drug items, wherein the preset condition is that the quantity corresponding to the replenishment drug items is not greater than a quantity threshold; Determine whether the storage size of each target drug item meets the corresponding quantity; If there is a target drug item whose storage size does not meet the corresponding quantity, the target drug item whose storage size does not meet the corresponding quantity is determined as the first target drug item, and the target drug items other than the first target drug item are determined as the second target drug item; Determine the current storage location corresponding to each of the second target pharmaceutical items as the corresponding storage location, and determine the storage location corresponding to each of the first target pharmaceutical items and the storage location corresponding to each of the remaining pharmaceutical items to obtain the storage location corresponding to each replenishment pharmaceutical item.

[0016] By adopting the above technical solution, the current storage location information of each replenishment drug item, including the storage location and storage location size, is obtained, and the refined management of the warehouse space is realized, so that the warehouse management personnel can clearly understand the capacity and usage of each storage location, so as to make more reasonable storage location allocation decisions. At the same time, the target drug items and the remaining drug items are screened out by preset conditions (such as the quantity corresponding to the replenishment drug item is not greater than the quantity threshold), and different treatment methods are adopted for them. For the second target drug item with a smaller quantity, the current storage location is directly used to reduce unnecessary movement and adjustment; while for the first target drug item and the remaining drug items that may need to be adjusted, more detailed storage location planning is carried out. For the first target drug item whose storage location size does not meet the corresponding quantity, the solution will re-determine its storage location to ensure that the drug can be reasonably stored, and will not be stacked too high or inconvenient to pick up due to too small storage location. At the same time, for the remaining drug items, storage locations will also be allocated according to their characteristics and needs, so as to further optimize the utilization of warehouse space.

[0017] In a possible implementation, determining the storage location corresponding to each of the first target drug items and the storage location corresponding to each of the remaining drug items includes: Determine the storage locations other than the storage location corresponding to the second target drug item as vacant storage locations; Sorting the quantities corresponding to each of the first target drug items and the quantities corresponding to each of the remaining drug items in descending order to obtain a target sequence; Based on the storage size corresponding to each free storage location, free storage locations are allocated to the quantity corresponding to each of the first target pharmaceutical items in the target sequence and to each of the remaining pharmaceutical items to obtain a storage location corresponding to each of the first target pharmaceutical items and a storage location corresponding to each of the remaining pharmaceutical items.

[0018] By adopting the above technical solution, all storage locations except the storage locations corresponding to the second target drug item are regarded as idle storage locations, which ensures the maximum utilization of storage location resources, thereby avoiding waste caused by vacant storage locations, and also provides sufficient selection space for the first target drug item and the remaining drug items that need to adjust the storage locations. The target sequence is obtained by sorting the first target drug item and the remaining drug items in order of quantity from large to small, and the storage locations are allocated using a simulated return algorithm in combination with the storage location size of the idle storage locations. This method that combines quantity sorting and intelligent algorithms can more efficiently find storage locations that meet demand, improving the accuracy and efficiency of storage location allocation.

[0019] In a second aspect, the present application provides a drug replenishment device, which adopts the following technical solution: A medicine replenishment device, comprising: An acquisition module, used to acquire current order data and current drug data corresponding to a current cycle, wherein the current order data includes order sub-data corresponding to each order in the current cycle, wherein the order sub-data includes drug items and the shipment volume corresponding to each drug item, and the current drug data includes the quantity, batch number and storage location corresponding to each drug item; A first determination module is used to determine the replenishment drug items in a future period and the quantity and batch number corresponding to each replenishment drug item based on the current order data and the current drug data; The second determination module is used to determine the storage location corresponding to each replenishment drug item; A generation module is used to generate a replenishment plan based on the replenishment drug items and the corresponding drug quantities, storage locations and batch numbers; An execution module is used to generate a replenishment task corresponding to each replenishment drug quality based on the replenishment plan, and execute the replenishment task.

[0020] In a third aspect, the present application provides an electronic device, which adopts the following technical solution: An electronic device, comprising: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the drug replenishment method described in the first aspect above.

[0021] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium, comprising: storing a computer program that can be loaded by a processor and execute the drug replenishment method described in the first aspect above.

[0022] In summary, this application includes the following beneficial technical effects: By analyzing the current order data (including the drug items and shipments under each order) and the current drug data (quantity, batch number, storage location) in real time, it is possible to accurately identify which drug items need to be replenished and the replenishment quantity required for each, avoiding the problem of excessive inventory or inventory shortage, thereby improving inventory turnover. The replenishment drug items, quantities and batch numbers are determined through an automated process, and a replenishment plan is immediately generated, which is then quickly converted into a replenishment task and executed, significantly reducing the waiting time from order processing to actual replenishment and improving overall operational efficiency. At the same time, when determining the replenishment drug items, the batch number corresponding to each replenishment drug item will also be determined, because different batch numbers may represent different production dates, expiration dates or production batches, which is of great significance for ensuring drug quality and patient safety. Through strict batch number management, the risk of using expired or unqualified drugs can be effectively avoided. The entire process is an automated and intelligent replenishment process, which reduces the labor cost in the drug replenishment process and reduces the possibility of human errors in the drug replenishment project. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a flowchart of a drug replenishment method provided in an embodiment of the present application; Figure 2 is a block diagram of a drug replenishment device provided in an embodiment of the present application; Figure 3 It is a schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The following is combined with Figure 1 -Attached Figure 3 This application is described in further detail.

[0025] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0026] The process of drug replenishment is generally to formulate a replenishment plan that includes the drug items and quantities to be replenished based on inventory conditions and sales forecasts, and then contact the selected supplier to place an accurate purchase order. After the replenished drugs arrive, the replenished drugs are placed in the corresponding storage locations. With the development of technology, existing replenishment plans are generally generated through electronic devices such as mobile phones. Electronic devices obtain sales data and analyze the sales of various types of drugs, including sales volume, sales speed, etc., and determine the types and quantities of drugs that need to be replenished through historical sales data and market demand forecasts. A replenishment plan is formulated based on the current inventory situation and sales forecasts. However, after the replenished drugs arrive, replenishment personnel are still required to place the arrived replenished drugs in storage locations, which requires a lot of labor costs.

[0027] In view of this, the present application embodiment provides a drug replenishment method, such as Figure 1 As shown, the method provided in the embodiment of the present application is performed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in the embodiment of the present application. The method includes steps S101 to S105, wherein: Step S101, obtaining current order data and current drug data corresponding to the current cycle.

[0028] Among them, the current order data includes the order sub-data corresponding to each order in the current cycle, the order sub-data includes the drug items and the shipment volume corresponding to each drug item, and the current drug data includes the quantity, batch number and storage location corresponding to each drug item. Specifically, the current order is the sum of all sub-orders in the current cycle, and the current cycle can be set according to actual conditions, which is not limited in the embodiments of the present application.

[0029] When there is a shipment of medicines, that is, when a sub-order is generated, the electronic device automatically records the time when the sub-order is generated and the content of the sub-order. The content of the sub-order is the shipped medicine items and the corresponding shipment volume of each medicine item. The sum of the sub-orders shipped in the current cycle is the current order. After the medicines are shipped, the quantities corresponding to each medicine item stored in the current medicine warehouse change. Therefore, the quantities, batch numbers and storage locations corresponding to each medicine item stored in the medicine warehouse at the current moment can be obtained. Among them, one medicine item corresponds to at least one storage location, and one medicine item corresponds to at least one batch number. The batch number is used to indicate the production date, expiration date and production batch of the medicine.

[0030] Step S102: Based on the current order data and the current drug data, determine the drug items to be replenished in the future period and the quantity and batch number corresponding to each drug item to be replenished.

[0031] After obtaining the current order data and current drug data corresponding to the current cycle, the replenishment drug items corresponding to the future cycle and the quantity and batch number corresponding to each replenishment drug item can be predicted. Specifically, the current order data is traversed, and for each drug item in the order, the replenishment demand quantity of each drug item is calculated based on its shipment quantity minus the quantity of the drug item in the current drug storage inventory. If the replenishment demand quantity of a drug item is greater than 0, it is marked as a drug item that needs to be replenished, and its replenishment quantity is recorded.

[0032] Obtain the batch number corresponding to the replenishment drug item corresponding to the historical period, and compare the batch number of each replenishment drug item in each historical period with the corresponding historical period to determine the production date of the latest batch corresponding to each replenishment drug item at the time of replenishment, and based on the production date of the latest batch corresponding to each replenishment drug item at the time of replenishment, determine the production date of the latest batch corresponding to each replenishment drug item in the current period, and combine the drug items to be replenished and the corresponding production date of the latest batch to obtain the quantity and batch number corresponding to each replenishment drug item.

[0033] Step S103: determine the storage location corresponding to each replenishment drug item.

[0034] Among them, each drug item currently corresponds to at least one storage location. When the drug is shipped, there will be some vacancies in the storage location corresponding to the shipped drug item. Therefore, the current vacant storage location space corresponding to each replenishment drug item is obtained, and the subspace occupied by a single drug corresponding to each replenishment drug item is obtained. Based on the quantity of each replenishment drug item and the subspace occupied by the corresponding single drug, the replenishment space corresponding to each replenishment drug item is obtained.

[0035] In order to facilitate the management of medicines, the medicines of the same replenishment medicine item are preferably placed in the same storage location or adjacent storage locations. Therefore, for any replenishment medicine item, the process of determining the storage location corresponding to the replenishment medicine item can be as follows: based on the replenishment space corresponding to the replenishment medicine item and the current storage location vacant space, determine whether the current storage location vacant space is not less than the replenishment space, so as to determine whether the replenishment quantity can be completely placed in the current storage location. If the current storage location vacant space is not less than the replenishment space, the replenishment medicine is placed in the current storage location; if the current storage location vacant space is less than the replenishment space, the adjacent free storage location of the current storage location is obtained, and based on the space difference between the current storage location vacant space and the replenishment space, a target storage location that is larger than the space difference and has a capacity closest to the space difference is selected from the adjacent free storage locations, and the replenishment medicine is placed in the current storage location and the target storage location.

[0036] Furthermore, when replenishment drugs are placed in the current storage location, drugs with earlier production dates corresponding to batch numbers are placed near the storage location exit, and drugs with later production dates corresponding to batch numbers are placed far from the storage location exit.

[0037] Step S104: Generate a replenishment plan based on the replenishment drug items and the corresponding drug quantities, storage locations, and batch numbers.

[0038] After obtaining each replenishment drug item, the corresponding drug quantity, storage location and batch number of each replenishment drug item, all drug items that need to be replenished, the corresponding replenishment quantity, storage location and batch number information are organized into a replenishment plan.

[0039] Step S105: Generate a replenishment task corresponding to each replenishment drug quality based on the replenishment plan, and execute the replenishment task.

[0040] Generate a replenishment task order for each replenishment drug item based on the replenishment plan, assign the replenishment task order to the warehouse staff, and instruct them to take out the corresponding quantity and batch number of drugs from the designated inventory location according to the requirements on the task order, and then place them in the designated replenishment storage location.

[0041] Furthermore, during the replenishment process, warehouse staff updates the drug storage inventory system in real time to ensure the accuracy and timeliness of inventory data. After replenishment is completed, electronic equipment reviews and confirms the updated data in the drug storage to ensure that all replenishment tasks have been completed.

[0042] The embodiment of the present application provides a drug replenishment method, which can accurately identify which drug items need to be replenished and the replenishment quantity required by each drug item by real-time analysis of current order data (including drug items and shipments under each order) and current drug data (quantity, batch number, storage location), avoiding the problem of excessive inventory or inventory shortage, thereby improving inventory turnover. The replenishment drug items, quantities and batch numbers are determined through an automated process, and a replenishment plan is immediately generated, which is then quickly converted into a replenishment task and executed, significantly reducing the waiting time from order processing to actual replenishment, and improving overall operational efficiency. At the same time, when determining the replenishment drug items, the batch number corresponding to each replenishment drug item will be determined at the same time, because different batch numbers may represent different production dates, expiration dates or production batches, which is of great significance for ensuring drug quality and patient safety. Through strict batch number management, the risk of using expired or unqualified drugs can be effectively avoided. The entire process is an automated and intelligent replenishment process, which reduces the labor cost in the drug replenishment process and reduces the possibility of human errors in the drug replenishment project.

[0043] In a possible implementation of the embodiment of the present application, in the above step S102, based on the current order data and the current drug data, determining the replenishment drug items in the future period and the quantity corresponding to each replenishment drug item may specifically include: Obtain historical order data, which includes order data corresponding to each historical period; Based on historical order data and current order data, predict future order sub-data corresponding to future periods; Based on the current order data, future order sub-data and current drug data, determine the replenishment drug items in the future period and the corresponding quantity of each replenishment drug item.

[0044] The electronic device automatically records the order data corresponding to each historical period and the current period, so that the historical order data corresponding to each historical period can be obtained to predict the future period and determine the replenishment drug items in the future period and the corresponding quantity of each replenishment drug item based on the historical order data. The order data includes the order sub-data corresponding to each order.

[0045] Specifically, historical order data corresponding to each historical period is obtained, and time series prediction methods (such as ARIMA, seasonal decomposition, machine learning models, etc.) are used to analyze the changing trends of the shipment volumes of each drug item in the historical order data. Based on the changing trends of the shipment volumes of each drug item and the shipment volumes of each drug item in the current order data, the prediction model is applied to generate the predicted shipment volumes of each drug item in the future period to obtain the future order sub-data corresponding to the future period.

[0046] Furthermore, after obtaining the future order sub-data corresponding to the future period, that is, after obtaining the predicted shipment volume corresponding to each drug item in the future period, for each drug item, the replenishment demand quantity of each drug item is calculated based on its predicted shipment volume minus the quantity of the drug item in the current drug warehouse inventory. If the replenishment demand quantity of a drug item is greater than 0, it is marked as a drug item that needs to be replenished, and its replenishment quantity and sum are recorded, thereby obtaining the replenishment drug items in the future period and the quantity corresponding to each replenishment drug item.

[0047] In a possible implementation of the embodiment of the present application, in the above steps, based on the historical order data and the current order data, the future order sub-data corresponding to the future period is predicted, wherein the prediction process of the future order sub-data corresponding to each drug item in the future period includes: Establish the probability curve corresponding to each historical period. The probability curve is used to characterize the probability density distribution of drug item shipments. Based on the probability curves corresponding to each historical period and current order data, predict the safe quantity of drug items in the future period; Based on the safety quantity corresponding to the drug item and the current order data, the future order sub-data corresponding to the drug item is determined.

[0048] Before predicting the future order sub-data corresponding to each drug item in the future cycle, the probability curve corresponding to the historical cycle is normally distributed based on the analysis of the historical order data. For example, the probability curve of the daily flat material picking operation of a single product is analyzed using the normal distribution method: by analyzing the picking order data from May to July, the following rules can be obtained from the form of the probability density distribution: 1) Concentration: The peak of the probability density curve is roughly located in the center (that is, the probability curve integral is 50%); 2) Symmetry: On both sides of the mean, the probability curve shows a downward trend, so it is normally distributed in form.

[0049] Therefore, for each drug item, its shipment data in each historical period can be extracted from the corresponding historical order data, and a shipment probability curve corresponding to each historical period can be established for the drug item using statistical methods (such as kernel density estimation, histogram smoothing, etc.). The shipment probability curve represents the probability density distribution at different shipments, reflecting the historical fluctuations in the shipment of the drug item.

[0050] Furthermore, the shipment data in each historical period can be extracted from the corresponding historical order data. According to the characteristics of the historical shipment data (i.e., normal distribution), a suitable probability density function is selected to fit the shipment of each drug item in each historical period, and the parameters of each probability density function are estimated using statistical methods (such as maximum likelihood estimation, moment estimation, etc.) to construct the probability curve corresponding to each historical period. Furthermore, the fitting effect of the probability curve can be evaluated by methods such as cross-validation to ensure the accuracy and reliability of the model.

[0051] Analyze the changing trend of shipments in the current order data, and combine it with the historical probability curve to predict the safe quantity of pharmaceutical items in future cycles. Among them, the safe quantity is usually a value that can cover most shipment situations. Specifically, obtain the preset confidence level corresponding to the future cycle, and based on the preset confidence level and the probability curve corresponding to each historical cycle, calculate the confidence level interval corresponding to the future cycle, and the confidence level interval is the safe quantity corresponding to the pharmaceutical item in the future cycle. Among them, the preset confidence level can be 95%, or it can be set according to actual conditions, which is not limited in the embodiments of the present application. It is worth noting that calculating the confidence level interval based on a probability curve with a normal distribution and a preset confidence level is a conventional technical means, which will not be elaborated in the embodiments of the present application.

[0052] In a possible implementation of the embodiment of the present application, in the above steps, when the historical order data includes the general replenishment quantity, emergency replenishment quantity and replenishment time of each drug item corresponding to each historical period, based on the probability curve corresponding to each historical period and the current order data, predicting the corresponding safe quantity of the drug item in the future period may specifically include: Based on the probability curves corresponding to each historical period, calculate the historical replenishment volume variance and historical replenishment volume mean; Divide each historical period into at least two historical sub-periods, and obtain the historical sub-orders corresponding to each historical sub-period, where the historical sub-orders include the historical sub-shipments corresponding to each drug item; Based on the historical order data, determine the corresponding historical sub-replenishment quantity of each drug item in each historical sub-period; Based on the historical sub-orders corresponding to each historical sub-period and the historical sub-replenishment quantities corresponding to each drug item, a first reference quantity of each drug item corresponding to each historical period is calculated; Calculate the average of the first reference amount of each drug item corresponding to each historical period to obtain the second reference amount corresponding to each drug item; Based on the second reference quantity corresponding to each drug item, determine the confidence level corresponding to the general future replenishment quantity in the future period; Based on the confidence level, the historical general replenishment volume corresponding to each historical period, the historical replenishment volume variance, and the historical replenishment volume mean, determine the future general replenishment confidence interval corresponding to the future period; Determine the future general replenishment quantity corresponding to the future general replenishment confidence interval; Based on the historical general replenishment quantity and historical emergency replenishment quantity corresponding to each historical period, determine the future emergency replenishment quantity corresponding to the future period; Determine the expected shipment volume for the current period based on the current order data and the probability curves corresponding to each historical period; Based on the estimated shipment volume, future general replenishment volume, and future emergency replenishment volume, determine the corresponding safe quantity of drug items in future cycles.

[0053] Among them, the general replenishment quantity is the quantity of initial replenishment within a certain cycle, and the emergency replenishment quantity is the quantity of replenishment of one or more drug items in the middle stage of a certain cycle.

[0054] Specifically, after obtaining the probability curves corresponding to each historical period, since the probability curves are normally distributed, the variance and mean of the replenishment quantity corresponding to each probability curve can be calculated. And according to the emergency replenishment moment corresponding to each historical period, each historical period is divided into at least two historical sub-periods.

[0055] Furthermore, for each historical sub-period, the historical sub-shipment volume corresponding to each drug item (i.e., the shipment volume in the sub-period) is extracted. Based on the historical sub-shipment volume and combined with the inventory change records, the corresponding historical sub-replenishment volume (i.e., the quantity required to be replenished in the sub-period) of each drug item in each historical sub-period is calculated.

[0056] For each drug item, in each historical sub-period, the first reference quantity is calculated based on the historical sub-shipment quantity and the historical sub-replenishment quantity, and based on the first reference quantity = historical sub-shipment quantity / historical sub-replenishment quantity. Further, after obtaining the first reference quantity corresponding to each historical period, the average of each first reference quantity in each historical sub-period can be calculated to obtain the second reference quantity corresponding to each historical period, and the second reference quantity represents a long-term average level of replenishment demand for the drug item.

[0057] Furthermore, based on the second reference quantity of each drug item, the second reference quantity corresponding to each drug item is used as the confidence level (such as 95% confidence level) for determining the future general replenishment quantity of the corresponding replenishment drug item. Furthermore, based on the confidence level, the historical general replenishment quantity, the variance and mean of the historical replenishment quantity, the confidence interval of the future general replenishment quantity is calculated. Specifically, for each replenishment drug item, based on the probability curves corresponding to each historical period, a historical target probability curve is fitted, and the historical target probability curve is normally distributed, and the historical target probability curve can characterize the probability density distribution of the average shipment volume in each historical period.

[0058] For each replenishment drug item, the confidence interval corresponding to the replenishment drug item is calculated based on the target formula and the confidence level corresponding to the replenishment drug item, where the target formula is: ,in, is the mean of the means corresponding to each probability curve, is the historical target probability curve, s is the mean of the replenishment quantity variance corresponding to each probability curve, and n is the number of historical cycles.

[0059] Furthermore, after obtaining the general replenishment confidence interval corresponding to each replenishment drug item, the sum of the replenishment quantities at the position corresponding to the historical target probability curve of the replenishment confidence interval is used as the future general replenishment quantity, and the relationship between the historical general replenishment quantity and the historical emergency replenishment quantity in each historical period is analyzed. Based on historical data and the current market environment, the emergency replenishment situation that may occur in the future period is predicted, and the future emergency replenishment quantity is estimated accordingly. Specifically, time series analysis can be used, combined with the current order data and the probability curve of the historical period, to predict the expected shipment volume in the future period.

[0060] Taking into account the future general replenishment volume, future emergency replenishment volume and expected shipment volume, as well as the safety inventory strategy of inventory management (such as safety days, safety inventory, etc.), calculate the safety quantity of each drug item in the future cycle. Among them, the safety quantity should ensure that within the predicted demand range, sufficient inventory levels can be maintained to avoid the risk of out-of-stock, while optimizing inventory costs.

[0061] In a possible implementation of the embodiment of the present application, in the above steps, based on the historical general replenishment quantities and the historical emergency replenishment quantities corresponding to each historical period, determining the future emergency replenishment quantity corresponding to the future period may specifically include: The correlation between the general replenishment quantity and the emergency replenishment quantity is determined based on Formula 1, where Formula 1 is: , is the correlation between general replenishment quantity and emergency replenishment quantity, n is the number of historical cycles, is the historical general replenishment quantity corresponding to the i-th historical period, is the average value of the historical general replenishment quantity corresponding to multiple historical periods, is the historical emergency replenishment quantity corresponding to the i-th historical period, is the average value of the historical emergency replenishment quantity corresponding to each historical period, is a constant; Determine whether the correlation is greater than a correlation threshold; If the correlation is greater than the correlation threshold, the first fitting parameter and the second fitting parameter are determined based on the historical order data corresponding to each historical period, and the future emergency replenishment quantity corresponding to the future period is determined based on the correlation and Formula 2, where Formula 2 is: ,in, is the future emergency replenishment quantity corresponding to the future cycle, is the first fitting parameter, is the correlation between general replenishment quantity and emergency replenishment quantity, is the general emergency replenishment quantity corresponding to the future cycle, is the second fitting parameter; If the correlation is not greater than the correlation threshold, each historical order data is analyzed to obtain the contribution coefficient between the historical general replenishment quantity average and the historical emergency replenishment quantity average, and the future emergency replenishment quantity corresponding to the future period is determined based on Formula 3, where Formula 3 is: ,in, is the future emergency replenishment quantity corresponding to the future cycle, is the contribution coefficient, To fine-tune the forecast value of emergency replenishment quantity based on general replenishment quantity and correlation.

[0062] When the general replenishment quantity is high in a cycle, there may be a large number of orders in the cycle, which greatly increases the emergency replenishment quantity. Therefore, the correlation between the general replenishment quantity and the emergency replenishment quantity is of great significance for predicting the future emergency replenishment quantity in the future cycle. Specifically, the correlation between the general replenishment quantity and the emergency replenishment quantity can be calculated by formula 1, where formula 1 is: ,in, is the correlation between general replenishment quantity and emergency replenishment quantity, n is the number of historical cycles, is the historical general replenishment quantity corresponding to the i-th historical period, is the average value of the historical general replenishment quantity corresponding to multiple historical periods, is the historical emergency replenishment quantity corresponding to the i-th historical period, is the average value of the historical emergency replenishment quantity corresponding to each historical period, is a constant. The i-th historical period is the order in which the historical periods are sorted according to the time sequence, and the i-th historical period is sorted according to the order.

[0063] Furthermore, after calculating the correlation between the general replenishment quantity and the emergency replenishment quantity, it can be determined whether the correlation is greater than the correlation threshold to determine the degree of influence of the general replenishment quantity on the emergency replenishment quantity. If the correlation is greater than the correlation threshold, it means that the general replenishment quantity has a deeper influence on the emergency replenishment quantity. Therefore, the future emergency replenishment quantity can be predicted based on each historical general replenishment quantity. Specifically, based on the historical order data corresponding to each historical period, the first fitting parameter and the second fitting parameter are determined, and the future emergency replenishment quantity corresponding to the future period is determined based on the correlation and formula 2, where formula 2 is: ,in, is the future emergency replenishment quantity corresponding to the future cycle, is the first fitting parameter, is the correlation between general replenishment quantity and emergency replenishment quantity, is the general emergency replenishment quantity corresponding to the future cycle, It is worth noting that for the second fitting parameter, n represents the nth historical period, from which it can be obtained that the current period is the n+1th period and the future period is the n+2th period.

[0064] If the correlation is not greater than the correlation threshold, it means that the general replenishment quantity has a low impact on the emergency replenishment quantity. Therefore, each historical order data can be analyzed to obtain the contribution coefficient between the historical general replenishment quantity average and the historical emergency replenishment quantity average, and the future emergency replenishment quantity corresponding to the future period can be determined based on Formula 3, where Formula 3 is: ,in, is the future emergency replenishment quantity corresponding to the future cycle, is the contribution coefficient, To fine-tune the forecast value of emergency replenishment quantity based on general replenishment quantity and correlation. It is worth noting that according to the forecast of general replenishment quantity And the degree of relevance (Although the correlation is low, it may still contain some useful information) to fine-tune the prediction of emergency replenishment. However, in the case of very low correlation (below a certain threshold), this function can be ignored.

[0065] In a possible implementation of the embodiment of the present application, in the above step S103, determining the storage location corresponding to each replenishment drug item includes: Get the current storage location information for each replenishment drug item; Filtering out target drug items that meet preset conditions from multiple replenishment drug items, and determining replenishment drug items other than the target drug items as remaining drug items, wherein the preset condition is that the quantity corresponding to the replenishment drug items is not greater than a quantity threshold; Determine whether the storage size of each target drug item meets the corresponding quantity; If there is a target drug item whose storage size does not meet the corresponding quantity, the target drug item whose storage size does not meet the corresponding quantity is determined as the first target drug item, and the target drug items other than the first target drug item are determined as the second target drug item; The current storage location corresponding to each second target pharmaceutical item is determined as the corresponding storage location, and the storage location corresponding to each first target pharmaceutical item and the storage location corresponding to each remaining pharmaceutical item are determined to obtain the storage location corresponding to each replenishment pharmaceutical item.

[0066] The current storage location information includes the storage location and storage location size, and the storage location size is the capacity of the storage location space.

[0067] Specifically, the storage location and storage size corresponding to each of the replenishment drug items are obtained, and all replenishment drug items are traversed, and those drug items whose replenishment quantity is not greater than the quantity threshold are screened out as "target drug items", and drug items greater than the quantity threshold are classified as "other drug items". Among them, the quantity threshold can be set according to actual conditions, and this embodiment of the application is not limited to this.

[0068] Furthermore, for the target drug items, check whether the current storage size corresponding to each target drug item meets the replenishment quantity. If not, mark the drug item as the "first target drug item"; if satisfied, mark it as the "second target drug item".

[0069] For each second target drug item: Since the replenishment quantity of the second target drug item can be directly stored in the current storage location, the current storage location is directly used as its corresponding storage location.

[0070] For each first target drug item: based on the replenishment quantity and storage location size requirements, find suitable vacant storage locations in the drug warehouse or readjust existing storage locations (such as merging storage locations adjacent to current storage locations) to store the replenishment drugs corresponding to the first target drug item, and record the new storage location information found as the new corresponding storage location for the first target drug item.

[0071] For each remaining drug item: Since the corresponding replenishment quantity of the remaining drug item is large, it can be directly arranged to a large storage location or designated area, or replenished in batches to multiple storage locations.

[0072] Furthermore, after obtaining the storage location information corresponding to each replenishment drug item, the current storage location and the replenishment storage location corresponding to each drug item are used as the final storage location corresponding to the drug item, and the final storage location information including the final storage location of each replenishment drug item is recorded.

[0073] A possible implementation of the embodiment of the present application, in the above steps, determining the storage location corresponding to each first target drug item and the storage location corresponding to each remaining drug item includes: Determine the storage locations other than the storage location corresponding to the second target drug item as vacant storage locations; Sorting the quantities corresponding to each first target drug item and the quantities corresponding to each remaining drug item in descending order to obtain a target sequence; Based on the storage size corresponding to each free storage location, free storage locations are allocated to the quantity corresponding to each first target drug item in the target sequence and each remaining drug item to obtain a storage location corresponding to each first target drug item and a storage location corresponding to each remaining drug item.

[0074] Specifically, all storage locations are traversed and the storage locations occupied by the second target drug items are excluded. The remaining storage locations except the storage locations occupied by the second target drug items are determined as vacant storage locations. The replenishment quantities are sorted in descending order according to the corresponding quantities of each first target drug item and other drug items. The sorting results form a target sequence, and each element in the sequence represents a drug item and its corresponding quantity.

[0075] Furthermore, a simulated return algorithm can be used to allocate storage locations. Specifically, a simulated "storage location allocation table" is set, which contains all free storage locations and their corresponding storage location sizes (such as capacity). Each drug item and its quantity in the target sequence is traversed. For each drug item, the largest storage location that can accommodate the quantity of the drug item is found from the free storage location list. If a suitable storage location is found, the storage location is allocated to the drug item and the storage location is removed from the free storage location list. If there is no large enough storage location in the current free storage location to accommodate the drug item, the drug item is split into multiple smaller storage locations. If there is an emergency, non-free storage locations can be temporarily used (such as by moving other drug items to make room). Repeat the above steps until all target drug items are allocated storage locations or cannot be further allocated. In the allocation process, multiple iterations and adjustments are performed according to actual conditions to optimize storage location utilization and reduce handling costs.

[0076] The above-mentioned embodiment introduces a drug replenishment method from the perspective of method flow, and the following embodiment introduces a drug replenishment device from the perspective of a virtual module or a virtual unit. Please refer to the following embodiment for details.

[0077] See also Figure 2 The drug replenishment device 20 may specifically include: an acquisition module 201, a first determination module 202, a second determination module 203, a generation module 204 and an execution module 205, wherein: A medicine replenishment device 20, comprising: The acquisition module 201 is used to acquire the current order data and current drug data corresponding to the current cycle. The current order data includes the order sub-data corresponding to each order in the current cycle. The order sub-data includes drug items and the shipment volume corresponding to each drug item. The current drug data includes the quantity, batch number and storage location corresponding to each drug item. A first determination module 202 is used to determine the replenishment drug items in the future period and the quantity and batch number corresponding to each replenishment drug item based on the current order data and the current drug data; The second determination module 203 is used to determine the storage location corresponding to each replenishment drug item; A generation module 204, for generating a replenishment plan based on the replenishment drug items and the corresponding drug quantities, storage locations and batch numbers; The execution module 205 is used to generate a replenishment task corresponding to each replenishment drug quality based on the replenishment plan, and execute the replenishment task.

[0078] In a possible implementation of the embodiment of the present application, when the first determination module 202 determines the replenishment drug items and the quantity corresponding to each replenishment drug item in the future period based on the current order data and the current drug data, it is specifically used to: Obtain historical order data, which includes order data corresponding to each historical period; Based on historical order data and current order data, predict future order sub-data corresponding to future periods; Based on the current order data, future order sub-data and current drug data, determine the replenishment drug items in the future period and the corresponding quantity of each replenishment drug item.

[0079] In a possible implementation of the embodiment of the present application, the first determination module 202 predicts the future order sub-data corresponding to the future period based on the historical order data and the current order data, wherein the prediction process of the future order sub-data corresponding to each drug item in the future period is specifically used to: Establish the probability curve corresponding to each historical period. The probability curve is used to characterize the probability density distribution of drug item shipments. Based on the probability curves corresponding to each historical period and current order data, predict the safe quantity of drug items in the future period; Based on the safety quantity corresponding to the drug item and the current order data, the future order sub-data corresponding to the drug item is determined.

[0080] In a possible implementation of the embodiment of the present application, when the historical order data includes the general replenishment quantity, emergency replenishment quantity, and replenishment time of each drug item corresponding to each historical period, the first determination module 202 predicts the safe quantity corresponding to the drug item in the future period based on the probability curve corresponding to each historical period and the current order data, specifically for: Based on the probability curves corresponding to each historical period, calculate the historical replenishment volume variance and historical replenishment volume mean; Divide each historical period into at least two historical sub-periods, and obtain the historical sub-orders corresponding to each historical sub-period, where the historical sub-orders include the historical sub-shipments corresponding to each drug item; Based on the historical order data, determine the corresponding historical sub-replenishment quantity of each drug item in each historical sub-period; Based on the historical sub-orders corresponding to each historical sub-period and the historical sub-replenishment quantities corresponding to each drug item, a first reference quantity of each drug item corresponding to each historical period is calculated; Calculate the average of the first reference amount of each drug item corresponding to each historical period to obtain the second reference amount corresponding to each drug item; Based on the second reference quantity corresponding to each drug item, determine the confidence level corresponding to the general future replenishment quantity in the future period; Based on the confidence level, the historical general replenishment volume corresponding to each historical period, the historical replenishment volume variance, and the historical replenishment volume mean, determine the future general replenishment confidence interval corresponding to the future period; Determine the future general replenishment quantity corresponding to the future general replenishment confidence interval; Based on the historical general replenishment quantity and historical emergency replenishment quantity corresponding to each historical period, determine the future emergency replenishment quantity corresponding to the future period; Determine the expected shipment volume for the current period based on the current order data and the probability curves corresponding to each historical period; Based on the estimated shipment volume, future general replenishment volume, and future emergency replenishment volume, determine the corresponding safe quantity of drug items in future cycles.

[0081] In a possible implementation of the embodiment of the present application, when the first determination module 202 determines the future emergency replenishment quantity corresponding to the future period based on the historical general replenishment quantity and the historical emergency replenishment quantity corresponding to each historical period, it is specifically used to: The correlation between the general replenishment quantity and the emergency replenishment quantity is determined based on Formula 1, where Formula 1 is: , is the correlation between general replenishment quantity and emergency replenishment quantity, n is the number of historical cycles, is the historical general replenishment quantity corresponding to the i-th historical period, is the average value of the historical general replenishment quantity corresponding to multiple historical periods, is the historical emergency replenishment quantity corresponding to the i-th historical period, is the average value of the historical emergency replenishment quantity corresponding to each historical period, is a constant; Determine whether the correlation is greater than a correlation threshold; If the correlation is greater than the correlation threshold, the first fitting parameter and the second fitting parameter are determined based on the historical order data corresponding to each historical period, and the future emergency replenishment quantity corresponding to the future period is determined based on the correlation and Formula 2, where Formula 2 is: ,in, is the future emergency replenishment quantity corresponding to the future cycle, is the first fitting parameter, is the correlation between general replenishment quantity and emergency replenishment quantity, is the general emergency replenishment quantity corresponding to the future cycle, is the second fitting parameter; If the correlation is not greater than the correlation threshold, each historical order data is analyzed to obtain the contribution coefficient between the historical general replenishment quantity average and the historical emergency replenishment quantity average, and the future emergency replenishment quantity corresponding to the future period is determined based on Formula 3, where Formula 3 is: ,in, is the future emergency replenishment quantity corresponding to the future cycle, is the contribution coefficient, To fine-tune the forecast value of emergency replenishment quantity based on general replenishment quantity and correlation.

[0082] In a possible implementation of the embodiment of the present application, when determining the storage location corresponding to each replenishment drug item, the second determination module 203 is specifically used to: Obtain the current storage location information corresponding to each replenishment drug item, including the storage location and storage size; Filtering out target drug items that meet preset conditions from multiple replenishment drug items, and determining replenishment drug items other than the target drug items as remaining drug items, wherein the preset condition is that the quantity corresponding to the replenishment drug items is not greater than a quantity threshold; Determine whether the storage size of each target drug item meets the corresponding quantity; If there is a target drug item whose storage size does not meet the corresponding quantity, the target drug item whose storage size does not meet the corresponding quantity is determined as the first target drug item, and the target drug items other than the first target drug item are determined as the second target drug item; The current storage location corresponding to each second target pharmaceutical item is determined as the corresponding storage location, and the storage location corresponding to each first target pharmaceutical item and the storage location corresponding to each remaining pharmaceutical item are determined to obtain the storage location corresponding to each replenishment pharmaceutical item.

[0083] In a possible implementation of the embodiment of the present application, when determining the storage location corresponding to each first target drug item and the storage location corresponding to each remaining drug item, the second determination module 203 is specifically configured to: Determine the storage locations other than the storage location corresponding to the second target drug item as vacant storage locations; Sorting the quantities corresponding to each first target drug item and the quantities corresponding to each remaining drug item in descending order to obtain a target sequence; Based on the storage size corresponding to each free storage location, free storage locations are allocated to the quantity corresponding to each first target drug item in the target sequence and each remaining drug item to obtain a storage location corresponding to each first target drug item and a storage location corresponding to each remaining drug item.

[0084] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0085] See also Figure 3 , the embodiment of the present application also introduces an electronic device from the perspective of a physical device, such as Figure 3 As shown, Figure 3 The electronic device 30 shown includes: a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, such as through a bus 302. Optionally, the electronic device 30 may also include a transceiver 304. It should be noted that in actual applications, the transceiver 304 is not limited to one, and the structure of the electronic device 30 does not constitute a limitation on the embodiments of the present application.

[0086] The processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processor 301 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0087] The bus 302 may include a path to transmit information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0088] The memory 303 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0089] The memory 303 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the contents shown in the above method embodiment.

[0090] The electronic devices include but are not limited to: mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc., and can also be servers, etc. Figure 3 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0091] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding content in the aforementioned method embodiment.

[0092] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0093] The above are only some implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A drug replenishment method, characterized in that: include: Obtaining current order data and current drug data corresponding to the current cycle, wherein the current order data includes order sub-data corresponding to each order in the current cycle, wherein the order sub-data includes drug items and the shipment volume corresponding to each drug item, and the current drug data includes the quantity, batch number, and storage location corresponding to each drug item; Based on the current order data and the current drug data, determine the replenishment drug items in the future period and the quantity and batch number corresponding to each of the replenishment drug items; Determine the storage location for each replenishment drug item; Generate a replenishment plan based on the replenishment drug items and the corresponding drug quantity, storage location and batch number; Based on the replenishment plan, a replenishment task corresponding to each replenishment drug quality is generated, and the replenishment task is executed.

2. The drug replenishment method according to claim 1, characterized in that: Based on the current order data and the current drug data, determining the replenishment drug items in the future period and the quantity corresponding to each replenishment drug item, including: Acquire historical order data, wherein the historical order data includes order data corresponding to each historical period; Based on the historical order data and the current order data, predict future order sub-data corresponding to a future period; Based on the current order data, the future order sub-data and the current drug data, the replenishment drug items in the future period and the quantity corresponding to each replenishment drug item are determined.

3. The drug replenishment method according to claim 2, characterized in that: The process of predicting the future order sub-data corresponding to the future period based on the historical order data and the current order data, wherein the prediction process of the future order sub-data corresponding to each drug item in the future period includes: Establishing probability curves corresponding to each historical period, wherein the probability curves are used to characterize the probability density distribution of the shipment volume of pharmaceutical items; Based on the probability curves corresponding to each historical period and the current order data, predict the safe quantity of the drug items in the future period; Based on the safety quantity corresponding to the pharmaceutical item and the current order data, the future order sub-data corresponding to the pharmaceutical item is determined.

4. The drug replenishment method according to claim 3, characterized in that: The historical order data includes the general replenishment quantity, emergency replenishment quantity and replenishment time of each drug item corresponding to each historical period. The prediction of the safe quantity corresponding to the drug item in the future period based on the probability curve corresponding to each historical period and the current order data includes: Based on the probability curves corresponding to each historical period, calculate the historical replenishment volume variance and historical replenishment volume mean; Divide each historical period into at least two historical sub-periods, and obtain historical sub-orders corresponding to each historical sub-period, wherein the historical sub-orders include the historical sub-shipments corresponding to each drug item; Based on the historical order data, determine the corresponding historical sub-replenishment quantity of each drug item in each historical sub-period; Based on the historical sub-orders corresponding to each historical sub-period and the historical sub-replenishment quantities corresponding to each drug item, a first reference quantity of each drug item corresponding to each historical period is calculated; Calculate the average of the first reference amount of each drug item corresponding to each historical period to obtain the second reference amount corresponding to each drug item; Determine the confidence level corresponding to the general future replenishment quantity in the future period based on the second reference quantity corresponding to each drug item; Determine a future general replenishment confidence interval corresponding to a future period based on the confidence level, the historical general replenishment quantity corresponding to each of the historical periods, the historical replenishment quantity variance, and the historical replenishment quantity mean; Determine the future general replenishment quantity corresponding to the future general replenishment confidence interval; Determine the future emergency replenishment quantity corresponding to the future period based on the historical general replenishment quantity and the historical emergency replenishment quantity corresponding to each historical period; Determine the expected shipment volume for the current period based on the current order data and the probability curves corresponding to each historical period; Based on the estimated shipment volume, the future general replenishment volume, and the future emergency replenishment volume, determine the safe quantity corresponding to the drug item in the future period.

5. The drug replenishment method according to claim 4, characterized in that: The determining of the future emergency replenishment quantity corresponding to the future period based on the historical general replenishment quantity and the historical emergency replenishment quantity corresponding to each historical period includes: The correlation between the general replenishment quantity and the emergency replenishment quantity is determined based on Formula 1, where Formula 1 is: , is the correlation between general replenishment quantity and emergency replenishment quantity, n is the number of historical cycles, is the historical general replenishment quantity corresponding to the i-th historical period, is the average value of the historical general replenishment quantity corresponding to multiple historical periods, is the historical emergency replenishment quantity corresponding to the i-th historical period, is the average value of the historical emergency replenishment quantity corresponding to each historical period, is a constant; Determining whether the degree of association is greater than a degree of association threshold; If the correlation is greater than the correlation threshold, the first fitting parameter and the second fitting parameter are determined based on the historical order data corresponding to each historical period, and the future emergency replenishment quantity corresponding to the future period is determined based on the correlation and Formula 2, where Formula 2 is: ,in, is the future emergency replenishment quantity corresponding to the future cycle, is the first fitting parameter, is the correlation between general replenishment quantity and emergency replenishment quantity, is the general emergency replenishment quantity corresponding to the future cycle, is the second fitting parameter; If the correlation is not greater than the correlation threshold, each historical order data is analyzed to obtain the contribution coefficient between the historical average of general replenishment quantities and the historical average of emergency replenishment quantities, and the future emergency replenishment quantity corresponding to the future period is determined based on Formula 3, where Formula 3 is: ,in, is the future emergency replenishment quantity corresponding to the future cycle, is the contribution coefficient, To fine-tune the forecast value of emergency replenishment quantity based on general replenishment quantity and correlation.

6. The drug replenishment method according to claim 1, characterized in that: Determining the storage location corresponding to each replenishment drug item includes: Obtaining current storage location information corresponding to each of the replenished drug items, wherein the current storage location information includes a storage location and a storage location size; Filtering out target drug items that meet preset conditions from multiple replenishment drug items, and determining the replenishment drug items other than the target drug items as remaining drug items, wherein the preset condition is that the quantity corresponding to the replenishment drug items is not greater than a quantity threshold; Determine whether the storage size of each target drug item meets the corresponding quantity; If there is a target drug item whose storage size does not meet the corresponding quantity, the target drug item whose storage size does not meet the corresponding quantity is determined as the first target drug item, and the target drug items other than the first target drug item are determined as the second target drug item; Determine the current storage location corresponding to each of the second target pharmaceutical items as the corresponding storage location, and determine the storage location corresponding to each of the first target pharmaceutical items and the storage location corresponding to each of the remaining pharmaceutical items to obtain the storage location corresponding to each replenishment pharmaceutical item.

7. The drug replenishment method according to claim 6, characterized in that: The determining of the storage location corresponding to each of the first target drug items and the storage location corresponding to each of the remaining drug items includes: Determine the storage locations other than the storage location corresponding to the second target drug item as vacant storage locations; Sorting the quantities corresponding to each of the first target drug items and the quantities corresponding to each of the remaining drug items in descending order to obtain a target sequence; Based on the storage size corresponding to each free storage location, free storage locations are allocated to the quantity corresponding to each of the first target pharmaceutical items in the target sequence and to each of the remaining pharmaceutical items to obtain a storage location corresponding to each of the first target pharmaceutical items and a storage location corresponding to each of the remaining pharmaceutical items.

8. A drug replenishment device, characterized in that: include: An acquisition module, used to acquire current order data and current drug data corresponding to a current cycle, wherein the current order data includes order sub-data corresponding to each order in the current cycle, wherein the order sub-data includes drug items and the shipment volume corresponding to each drug item, and the current drug data includes the quantity, batch number and storage location corresponding to each drug item; A first determination module is used to determine the replenishment drug items in a future period and the quantity and batch number corresponding to each replenishment drug item based on the current order data and the current drug data; The second determination module is used to determine the storage location corresponding to each replenishment drug item; A generation module is used to generate a replenishment plan based on the replenishment drug items and the corresponding drug quantities, storage locations and batch numbers; An execution module is used to generate a replenishment task corresponding to each replenishment drug quality based on the replenishment plan, and execute the replenishment task.

9. An electronic device, characterized in that: The electronic device includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the drug replenishment method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed in a computer, the computer is caused to execute the medicine replenishment method according to any one of claims 1 to 7.

Images