CN116258444A - Inventory management method and system for short-shelf-life commodities - Google Patents
Inventory management method and system for short-shelf-life commodities Download PDFInfo
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Abstract
The invention relates to the field of warehouse management, and discloses a method and a system for managing inventory of commodities with short shelf life, wherein the method comprises the following steps: acquiring inventory management information of all warehouse commodities; generating commodity demand of each warehouse in a future preset time period based on the historical sales list of each warehouse; generating expected turnover quantity of each warehouse for various commodities based on inventory of various commodities and commodity demand in a future preset time period; determining the actual turnover number of each warehouse for various commodities based on the current quality guarantee remaining time and the position information of the current various commodities; and generating an inventory turnover list of each warehouse for each commodity based on the actual turnover number of each warehouse for each commodity, and sending the inventory turnover list to a mobile terminal of a warehouse manager. By implementing the technical scheme provided by the application, the problem that the mode of solving the inventory problem by the existing warehouse management software is single is solved.
Description
Technical Field
The application relates to the field of warehouse management, in particular to a method and a system for managing inventory of short-shelf-life commodities.
Background
The short-shelf-life commodities are similar to fruits and vegetables, cakes, flowers and the like, and along with the development of society and the continuous improvement of living standard of people, the electronic commerce industry based on the network also develops rapidly, and people are more and more used to buy the commodities through electronic commerce websites.
In the face of rapidly growing commodity orders, the problem that partial commodity inventory is accumulated or partial commodity inventory is insufficient frequently occurs in a warehouse, particularly for short-shelf-life commodities, the condition that the commodity inventory is accumulated to cause expiration is easy to occur due to the defect of short shelf life, and large loss is caused to merchants, and the function of the existing warehouse management software is that when a certain commodity is sold, if the warehouse is in a shortage state, the warehouse with nearby inventory can be searched for emergency.
The inventor considers that the current warehouse management software can search nearby warehouses with stock for emergency only when the stock management function is based on the phenomenon that the current warehouses are out of stock, and the mode for solving the stacking problem is single for warehouses with too many stacked short shelf life commodities.
Disclosure of Invention
The invention aims to solve the problem that the mode of solving the stacking problem is single for warehouses with too many short shelf life commodities, and provides a method and a system for inventory management of the short shelf life commodities.
The above object of the present invention is achieved by the following technical solutions:
in a first aspect, the present application provides a method for inventory management of short shelf life commodities, applied to a server, the method comprising: acquiring inventory management information of all warehouse commodities, wherein the inventory management information comprises inventory lists, historical sales lists, current quality guarantee remaining duration and position information of all commodities; generating commodity demand of each warehouse in a future preset time period based on the historical sales list of each warehouse; generating expected turnover quantity of each warehouse for various commodities based on inventory of various commodities and commodity demand in a future preset time period; determining the actual turnover number of each warehouse for various commodities based on the current quality guarantee remaining time and the position information of the current various commodities; and generating an inventory turnover list of each warehouse for each commodity based on the actual turnover number of each warehouse for each commodity, and sending the inventory turnover list to a mobile terminal of a warehouse manager.
By adopting the technical scheme, the server counts the inventory management information of the commodities in all places of warehouses, including the inventory list, the historical sales list, the current quality guarantee remaining duration and the position information of all kinds of commodities. And preliminarily counting the commodity demand of each warehouse in a future preset time period according to the historical sales list of each warehouse. According to the inventory of various commodities and the commodity demand of each warehouse in a preset time period in the future, the expected turnover number of various commodities in each warehouse is generated, and then the commodities expected to be transported are screened according to the remaining quality guarantee period, the position information and the transportation cost of the commodities, so that the commodities unsuitable for transportation are removed. The server counts the inventory management information of each warehouse every day in real time, predicts the commodity demand of each warehouse according to the inventory management information, and adjusts the inventory of each warehouse. The warehouse management software solves the technical problems that the existing warehouse management software only searches nearby warehouses with stock for emergency when the stock management function is used for carrying out the stock shortage according to the current warehouse, and the mode for solving the stacking problem is single for the warehouses with too many short shelf life commodities.
Optionally, the generating, based on the historical sales listing of each warehouse, the commodity demand of each warehouse in the future preset time period includes: acquiring a first historical sales list of each warehouse in a recent preset time period; acquiring a second historical sales list of each warehouse in a plurality of continuous histories within the same preset time period; and generating commodity demand of each warehouse in a future preset time period according to the preset weight proportion based on the first historical sales list and the second historical sales list of each warehouse.
By adopting the technical scheme, the server acquires a recent historical sales list and a historical sales list of the same period in the past year of each warehouse, and predicts commodity demand of each warehouse in the future time period according to the historical sales lists of the two time periods with different weights. The warehouse manager can restock goods according to the generated commodity demand, so that the manager can manage the inventory better.
Optionally, the step of generating the commodity demand of each warehouse in the future preset time period based on the first historical sales list and the second historical sales list of each warehouse according to the preset weight ratio includes: acquiring holiday information of a preset time period in the future; acquiring a third historical sales list of each warehouse corresponding to the holiday of the past year; generating a holiday commodity demand list of each warehouse in a future preset time period based on the third historical sales list; and correcting the commodity demand of each warehouse in a future preset time period based on the holiday commodity demand list of each warehouse.
By adopting the technical scheme, the server can judge whether a special holiday exists in a preset time period in the future, if the special holiday exists, the server can search a historical sales list of the annual holiday period, screen out commodities with commodity sales greatly influenced by the holiday according to the historical sales list, generate a holiday commodity demand list, and correspondingly adjust commodity demands of all warehouses in the preset time period in the future according to the holiday commodity demand list. The special condition of holidays is considered, the condition that inventory is insufficient due to commodity order explosion is avoided, and the experience of customers is influenced. The warehouse manager can manage the inventory better, and the experience of clients is improved.
Optionally, the determining the actual turnover number of each warehouse for each commodity based on the current quality guarantee remaining duration and the position information of each commodity comprises: acquiring maximum quality guarantee time, maximum net profit value, storage cost information and turnover cost information of the commodity; generating a proportionality coefficient based on the current quality guarantee remaining time and the maximum quality guarantee time of the commodity; the proportionality coefficient is the ratio of the current quality guarantee remaining time length to the maximum quality guarantee time length; generating a net profit value for the commodity based on the scaling factor of the commodity, the stored cost information and the maximum net profit value; obtaining a commodity transfer quantity correction value based on the net profit value, turnover cost information and position information of the commodity and a preset commodity transfer correction function, wherein the commodity transfer correction function meets the following formula:
f(a,b,c)＝g(a)+h(b)*y(c)
Wherein a, b, c are net profit value, turnover cost information and location information factors, respectively; g (a) is a maximum net profit value correction function, h (b) is a turnover cost information correction function, and y (c) is a position information correction function; and determining the actual turnover quantity of each warehouse for various commodities based on the commodity transfer quantity correction value.
By adopting the technical scheme, the commodity with short shelf life mostly has insufficient freshness along with the reduction of shelf life, and the commodity needs to be subjected to price reduction treatment. The server initially estimates the profit value of the commodity according to the proportion function aiming at the quality guarantee remaining time of each type of commodity, and subtracts the daily storage cost to obtain the net profit value of the commodity. And warehouse management personnel can judge whether the commodity is still necessary to be left in the warehouse according to the net profit value, so that the warehouse management personnel can clean the warehouse at regular time. And the efficiency of transaction processing by warehouse management personnel is improved. The server obtains the net profit value, turnover cost information and position information of the commodities in each warehouse, and processes the commodities by using a preset transfer correction function to generate a commodity transfer correction function result. And comprehensively considering whether the commodity can be circulated according to the commodity transferring result. The diversion correction function can be adjusted by warehouse manager according to market conditions at that time. The perfect transferring system is more beneficial for warehouse management personnel to judge whether the commodity needs to be transferred or not, and cost is saved more how to transfer. And the quality and the efficiency of warehouse management are improved.
Optionally, the step of generating the net profit value of the commodity based on the commodity scaling factor, the stored cost information and the maximum net profit value includes: generating a profit value for the commodity based on the product of the scaling factor and the maximum net profit value; generating a cost value for the commodity based on the stored cost information; judging whether the profit value of the commodity is larger than the cost value of the commodity, and if the profit value of the commodity is larger than the cost value of the commodity, generating a net profit value of the commodity; if the profit value of the commodity is not greater than the cost value of the commodity, the net profit value of the commodity is not generated.
By adopting the technical scheme, the server obtains the proportionality coefficient, the storage cost information and the maximum net profit value of each commodity every day, the product of the proportionality coefficient and the maximum net profit value subtracts the storage cost of each commodity, and if the result is smaller than zero, the situation that the loss occurs to the commodity is indicated. The warehouse manager can find the corresponding commodity according to the profit value and process the commodity. Goods unsuitable for transfer are screened in advance, the workload of the server is reduced, and the server is facilitated to process data rapidly.
Optionally, the step of determining the actual turnover number of each warehouse for each type of commodity based on the commodity transfer amount correction value includes: obtaining a commodity transfer correction function result; if the numerical value of the commodity transferring correction function is larger than a preset threshold value, the actual turnover number of the commodity is reduced; and if the numerical value of the commodity transferring correction function is not greater than the preset threshold value, transferring the commodity.
According to the technical scheme, after the server calculates the result of the commodity transfer correction function, commodities unsuitable for transfer and commodities suitable for transfer are preliminarily screened out according to the value of the result. And generates an inventory turnover list and transmits the inventory turnover list to the mobile terminal of the server. Warehouse manager will review the inventory turnover list, and the inventory turnover list is produced by server automatic processing all kinds of information and data, need not artifical the participation, has practiced thrift a large amount of manpower, materials financial resources.
Optionally, the step of determining the actual turnover number of each warehouse for each type of commodity based on the commodity transfer quantity correction value comprises the following steps: based on the current quality guarantee remaining time of the commodities, correcting the actual turnover quantity of each warehouse for various commodities; and if the current quality guarantee remaining duration of the commodity is smaller than the preset time threshold, preferentially matching the commodity into a warehouse with large corresponding commodity demand.
By adopting the technical scheme, the server correspondingly adjusts the actual turnover number of each warehouse for various commodities according to the current quality guarantee remaining duration of the commodities. If the commodities in the warehouse need to be transferred to another warehouse, the commodities with shorter current quality guarantee residual duration are preferentially transferred to the warehouse with larger corresponding commodity demand, so that the commodities can be conveniently and rapidly sold. The method is beneficial to reserving more time to deal with emergency conditions, the commodity is sold more quickly in a short time, the condition that the commodity is placed for too long to influence sales is reduced, and the method is beneficial to improving the profit of enterprises.
In a second aspect, the present invention provides an inventory management system for short shelf life merchandise, the server comprising: the acquisition module is used for acquiring inventory management information of all warehouse commodities, wherein the inventory management information comprises inventory lists, historical sales lists, current quality guarantee remaining duration and position information of all commodities; the processing module is used for generating commodity demand of each warehouse in a future preset time period based on the historical sales list of commodities in each warehouse; the processing module is also used for generating the expected turnover number of each warehouse for various commodities based on the inventory of various commodities and the commodity demand in a preset time period in the future; the processing module is also used for acquiring the current quality guarantee remaining duration and position information of the commodities in each warehouse and determining the actual turnover number of the commodities in each warehouse; the processing module is also used for generating an inventory turnover list of each warehouse for various commodities based on the actual turnover quantity of each warehouse for various commodities; and the sending module is used for sending the inventory turnover list to the mobile terminal of the warehouse manager.
By adopting the technical scheme, the server comprises an acquisition module, a sending module and a processing module. After field personnel submit data information, each module cooperates with each other to operate, so that information is rapidly transmitted to the inner industry end of the server, and orderly work of each module improves the efficiency of flow operation of transactions. The efficient processing mode improves the efficiency of warehouse inventory operation.
In a third aspect, the present invention provides an electronic device comprising a processor, a memory, a user interface and a network interface, the memory being for storing instructions, the user interface and the network interface being for communicating to other devices, the processor being for executing the instructions stored in the memory to cause the electronic device to perform a method according to any one of the first aspects of the present application.
In a fourth aspect of the present application there is provided a computer readable storage medium storing instructions which, when executed, perform the method steps of any of the first aspects of the present application.
In summary, the present application includes the following beneficial technical effects:
the server reasonably predicts commodity demands of all warehouses in a future time period according to algorithm programs in the system by acquiring inventory management information of all warehouses. And generating the actual turnover number of the commodities in each warehouse according to the commodity demand in each warehouse and the inventory in each warehouse. And judging whether commodity transfer is cost-effective or not according to the cost of transfer and the profit situation of the commodity, and finally generating an inventory turnover list. The problem that conventional repository management software cannot provide a specific solution is solved. According to the demand of the short-shelf-life commodities of each warehouse in the future time period, the short-shelf-life commodities of each warehouse are transferred, so that the full coverage of warehouse inventory management is realized, a large amount of manpower and material resources are saved, and the standardization of warehouse inventory management is facilitated.
Drawings
FIG. 1 is a first flow chart of a method according to an embodiment of the present application.
Fig. 2 is a schematic block diagram of an embodiment of the present application.
Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Reference numerals illustrate: 11. an acquisition module; 12. a transmitting module; 13. a processing module; 500. an electronic device; 501. a processor; 502. a communication bus; 503. a user interface; 504. a network interface; 506. a memory.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present application, but not all embodiments.
In the description of embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described herein as "such as" or "for example" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "or" for example "is intended to present related concepts in a concrete fashion.
In the description of the embodiments of the present application, the term "plurality" means two or more. For example, a plurality of systems means two or more systems, and a plurality of screen terminals means two or more screen terminals. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating an indicated technical feature. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.
An embodiment of the application provides a method for managing inventory of short-shelf-life commodities, which is applied to a server. As shown in fig. 1, the method comprises steps S101-S105.
Step S101, acquiring inventory management information of all warehouse commodities, wherein the inventory management information comprises inventory lists, historical sales lists, current quality guarantee remaining duration and position information of all kinds of commodities.
Step S102, based on the historical sales listing of each warehouse, commodity demand of each warehouse in a future preset time period is generated.
Step S103, based on the inventory list of various commodities and the commodity demand in a preset time period in the future, the expected turnover number of various warehouses for various commodities is generated.
Step S104, determining the actual turnover number of each warehouse for various commodities based on the current quality guarantee remaining duration and the position information of the current various commodities.
And step S105, based on the actual turnover number of each warehouse for each type of commodity, generating an inventory turnover list of each warehouse for each type of commodity, and transmitting the inventory turnover list to a mobile terminal of a warehouse manager.
Specifically, the commodities of the present application all refer to short shelf life commodities. The inventory includes an inventory of each warehouse for each type of commodity. The historical sales listing includes a daily inventory sales listing for each warehouse. The current quality guarantee remaining time is the time when the distance of the commodity is out of date, the position information indicates the position information of the commodity in the warehouse to which the commodity belongs, and the commodity demand is the number of demands of each warehouse for each type of commodity in the future preset time. The expected turnover number is the number of warehouses or offwarehouses each required for various types of commodities. The actual turnover number is the number of the warehouses which are required to be put in or taken out of the warehouse for various commodities after being analyzed and processed by the server. The inventory turnover list is a commodity list of various warehouses which need to be put in or put out of the warehouse for various commodities.
For example, the server obtains inventory of goods in the three warehouses a, b, and c, historical sales inventory of goods in the three warehouses a, b, and c each day, and current remaining duration and location information for the goods in the three warehouses a, b, and c. And generating commodity demand of each of the first warehouse, the second warehouse and the third warehouse according to the daily historical sales listing of the first warehouse, the second warehouse and the third warehouse. And determining the actual turnover quantity of each warehouse for various commodities according to the inventory of the commodities in the first warehouse, the second warehouse and the third warehouse and the commodity demand. And determining the commodity which can be transferred and a commodity transferring path according to the current quality guarantee remaining duration and the position information of the commodity, and generating an inventory turnover list. And sends the inventory turnover list to the mobile terminal of the warehouse manager. All kinds of commodity transfer paths and quantity of the first warehouse, the second warehouse and the third warehouse on the whole inventory turnover list are generated by a server through the acquired information processing, and the related algorithm programs are all existing programs, so that manual participation is not needed, and the cost of manpower and material resources is saved.
Based on the historical sales listing of each warehouse, generating the commodity demand of each warehouse in a future preset time period comprises: acquiring a first historical sales list of each warehouse in a recent preset time period; acquiring a second historical sales list of each warehouse in a plurality of continuous histories within the same preset time period; and generating commodity demand of each warehouse in a future preset time period according to the preset weight proportion based on the first historical sales list and the second historical sales list of each warehouse.
For example, the server obtains inventory of goods for the three warehouses A, B, and C. A historical sales listing of the first 10 days and a historical sales listing of the last and last 10 days of the same date are obtained for the three warehouses a, b, and c. The historical sales list of the first 10 days accounts for 70% weight, the historical sales list of the last year and the last 10 days of the same date respectively accounts for 15% weight, the number of various commodities of the first 10 days is multiplied by 0.7, the number of commodities of the last year and the last 10 days of the same date are multiplied by 0.15 respectively, and the commodity number of the first, second and third warehouse of the new 10 days in the future is obtained to be the commodity demand. The preset weight ratio can be set by warehouse manager according to market. And judging the commodity demand of the future market according to the sales condition of the recent market, wherein the commodity demand prediction accuracy is higher under the condition that the external environment is not greatly changed. If seasonal replacement occurs, the commodity demand is calculated by continuously using a plurality of historical sales lists of all warehouses in the same preset time period, so that the accuracy of commodity demand prediction is improved.
The step of generating the commodity demand of each warehouse in the future preset time period according to the preset weight ratio based on the first historical sales list and the second historical sales list of each warehouse comprises the following steps: acquiring holiday information of a preset time period in the future; acquiring a third historical sales list of each warehouse corresponding to the holiday of the past year; generating a holiday commodity demand list of each warehouse in a future preset time period based on the third historical sales list; and correcting the commodity demand of each warehouse in a future preset time period based on the holiday commodity demand list of each warehouse.
For example, there are cases where sales of specific commodities are suddenly increased in specific holidays, and sales of other conventional commodities are affected by specific holidays. After commodity demand of the first warehouse, the second warehouse and the third warehouse in the future 10 days is generated, the server also judges whether holidays exist in the future 10 days, and if not, the commodity demand orders of the first warehouse, the second warehouse and the third warehouse are not processed; if the holiday exists, historical sales lists of the first warehouse, the second warehouse and the third warehouse with the same holiday period are obtained, and commodity demand lists of the holiday of the first warehouse, the second warehouse and the third warehouse are generated. And correcting the commodity demand of the first warehouse, the second warehouse and the third warehouse according to the holiday commodity demand list of the first warehouse, the second warehouse and the third warehouse. When predicting commodity demand in future market, the server fully considers special conditions of Chinese traditional holidays and adjusts commodity demand according to big data, and the related algorithm programs are all existing programs.
Based on the current quality guarantee remaining time and the position information of the current various commodities, determining the actual turnover number of each warehouse for the various commodities comprises the following steps: acquiring maximum quality guarantee time, maximum net profit value, storage cost information and turnover cost information of the commodity; generating a proportionality coefficient based on the current quality guarantee remaining time and the maximum quality guarantee time of the commodity; the proportionality coefficient is the ratio of the current quality guarantee remaining time length to the maximum quality guarantee time length; generating a net profit value for the commodity based on the scaling factor of the commodity, the stored cost information and the maximum net profit value; obtaining a commodity transfer quantity correction value based on the net profit value, turnover cost information and position information of the commodity and a preset commodity transfer correction function, wherein the commodity transfer correction function meets the following formula:
f(a,b,c)＝g(a)+h(b)*y(c)
Wherein a, b, c are net profit value, turnover cost information and location information factors, respectively; g (a) is a maximum net profit value correction function, h (b) is a turnover cost information correction function, and y (c) is a position information correction function; and determining the actual turnover quantity of each warehouse for various commodities based on the commodity transfer quantity correction value.
For example, after the server generates commodity demand amounts of three warehouses a, b and c for 10 days in the future, the server calculates the profit value of each commodity according to the maximum quality guarantee period, the current quality guarantee remaining period and the maximum net profit value of each commodity. The maximum quality guarantee period of the commodity No. 1 is 10 days, and the maximum net profit value is determined to be 10 yuan according to the current market quotation and the profit when the commodity is freshest. If the current shelf life remains for 5 days, the proportionality coefficient is calculated to be 0.5 according to the algorithm in the prior art. The net profit value for commodity number 1 is the product of the scaling factor and the maximum net profit value is equal to 5. g (a) the maximum net-profitability value correction function may be the net-profitability value factor a multiplied by 1.1.
h (b) the recurring cost information modification function may be the recurring cost information factor b multiplied by 0.9.y (c) the location information correction function may be the location information factor c multiplied by 0.7. The turnover cost information factor is the price of 1 km for each commodity, and the position information factor is the distance unit from the commodity to the warehouse, which is required to be transported, which is kilometer. The numbers 1.1, 0.9, 0.7 can be adjusted by warehouse manager according to market conditions. And the server comprehensively considers the situation that the transfer of the commodity can not have loss according to the net profit value, the turnover cost information and the position information of the commodity, and the commodity is transferred to the optimal solution of the warehouse. The program algorithm of the commodity transfer correction function is in the prior art, and can be set by warehouse management personnel according to market quotations and national policies, so that the warehouse transfer personnel do not rely on market experience to transfer the inventory, but a server generates a transfer scheme with the lowest inventory transfer cost based on big data of historical commodity sales and inventory information, and compared with manpower, the method has higher efficiency.
The step of generating a net profit value for the commodity based on the commodity scaling factor, the stored cost information, and the maximum net profit value comprises: generating a profit value for the commodity based on the product of the scaling factor and the maximum net profit value; generating a cost value for the commodity based on the stored cost information; judging whether the profit value of the commodity is larger than the cost value of the commodity, and if the profit value of the commodity is larger than the cost value of the commodity, generating a net profit value of the commodity; if the profit value of the commodity is not greater than the cost value of the commodity, the net profit value of the commodity is not generated.
Specifically, when generating a net profit value for the commodity, the server preferentially calculates the product of the scaling factor and the maximum net profit value, and generates the profit value of the commodity. And subtracting the storage cost of the commodity from the profit value, and judging whether the result is larger than a preset value. The commodity being greater than the preset value indicates that the commodity has a transportation condition. The fact that the commodity is larger than the preset value indicates that the commodity has a defect condition, and warehouse management personnel are required to process the commodity.
The step of determining the actual turnover number of each warehouse for various commodities based on the commodity transfer amount correction value comprises the following steps: judging whether the numerical value of the commodity transfer correction function is larger than a preset threshold value or not; if the numerical value of the commodity transferring correction function is larger than a preset threshold value, the actual turnover number of the commodity is reduced; and if the numerical value of the commodity transferring correction function is not greater than the preset threshold value, transferring the commodity.
For example, the server determines whether the commodity transfer is profitable based on the value of the generated commodity transfer correction function. If the commodity 1 has a shelf life of 2 days, the transportation time is one day. Increased transit time can result in additional storage costs and reduced profitability, as well as costs associated with commodity transit. When the cost exceeds the commodity profit value, the server will not list the commodity turnover list. The system has great assistance to the management cost of the warehouse, and saves the cost of manpower and material resources.
Based on the commodity transfer quantity correction value, the step of determining the actual turnover quantity of each warehouse for various commodities comprises the following steps: based on the current quality guarantee remaining time of the commodities, correcting the actual turnover quantity of each warehouse for various commodities; and if the current quality guarantee remaining duration of the commodity is smaller than the preset time threshold, preferentially matching the commodity into a warehouse with large corresponding commodity demand.
Specifically, after commodity transfer, whether the commodity can be sold in time needs to be considered, and particularly for some commodities with a near shelf life, the reduction of the shelf life can influence the purchasing desire of customers. After determining the actual turnover number of each warehouse to various commodities, the server searches the current quality guarantee remaining duration of the commodities to be transported, and if the remaining quality guarantee duration is smaller than a preset time threshold, the commodities are preferentially matched into the warehouse with large corresponding commodity demand, so that the commodities can be sold better.
The server automatically predicts the commodity demand of each warehouse for various commodities according to the historical sales information of each warehouse, and generates a reasonable inventory turnover list by combining the commodity demand and the commodity-related cost information and the position information. Warehouse management personnel better turnover short-shelf-life commodities according to an inventory turnover list, turnover cost is saved, and a specific solution is provided for transferring the short-shelf-life commodities of all warehouses according to the demand of the short-shelf-life commodities of all warehouses in a future time period.
As shown in fig. 2, which shows a schematic block flow diagram provided in an embodiment of the present application, a server includes: the acquiring module 11 is configured to acquire inventory management information of each warehouse commodity, where the inventory management information includes an inventory list, a historical sales list, a current quality guarantee remaining duration and location information of each commodity; the processing module 12 is used for performing character string verification based on the acquired identity verification information; the obtaining module 11 is further configured to obtain, at an outside end of the server, a historical sales list based on each warehouse by an outside person, and generate a commodity demand of each warehouse in a preset time period in the future; the processing module 12 is further configured to generate an expected turnover number of each warehouse for each type of commodity based on the inventory of each type of commodity and the commodity demand in a preset time period in the future; the processing module 12 is further used for determining the actual turnover number of each warehouse for various commodities based on the current quality guarantee remaining duration and the position information of the current various commodities; the processing module 12 is further configured to generate an inventory turnover list of each warehouse for each type of commodity based on the actual turnover number of each warehouse for each type of commodity; the sending module 13 is used for sending the inventory turnover list to a mobile terminal of a warehouse manager.
In another embodiment, the obtaining module 11 is further configured to obtain a first historical sales listing of each warehouse within a recent preset time period; the obtaining module 11 is further configured to obtain a second historical sales listing of each warehouse in a continuous plurality of histories within the same preset time period; the processing module 12 is further configured to generate, based on the first historical sales listing and the second historical sales listing of each warehouse, a commodity demand of each warehouse in a future preset time period according to a preset weight ratio.
In another embodiment, the obtaining module 11 is further configured to obtain holiday information of a future preset time period; the obtaining module 11 is further configured to obtain a third historical sales listing of each warehouse corresponding to the holiday in the past year; the processing module 12 is further configured to generate a holiday commodity demand list of each warehouse for a future preset period of time based on the third historical sales listing; the processing module 12 is further configured to correct the commodity demand of each warehouse in a future preset time period based on the holiday commodity demand list of each warehouse.
In another embodiment, the obtaining module 11 is further configured to obtain a maximum quality guarantee period, a maximum net profit value, storage cost information, and turnover cost information of the commodity; the processing module 12 is further configured to generate a scaling factor based on the current shelf life remaining time and the maximum shelf life of the commodity; the processing module 12 is also configured to generate a net profit value for the commodity based on the commodity scaling factor, the stored cost information, and the maximum net profit value. The processing module 12 is also configured to generate a commodity transfer correction function based on the net profit value, the turn-around cost information, and the location information for the commodity. The processing module 12 is also configured to determine the actual turnover number of each warehouse for each type of commodity based on the commodity transfer amount correction value.
In another embodiment, the processing module 12 is further configured to generate a profit value for the commodity based on the product of the scaling factor and the maximum net profit value; the processing module 12 is further configured to generate a cost value for the commodity based on the stored cost information; the processing module 12 is further configured to determine whether the profit value of the commodity is greater than the cost value of the commodity.
In another embodiment, the processing module 12 is further configured to determine whether the value of the commodity transfer correction function is greater than a preset threshold.
In another embodiment, the processing module 12 is further configured to modify the actual turnover number of each warehouse for each type of commodity based on the current remaining length of the commodity.
It should be noted that: in the device provided in the above embodiment, when implementing the functions thereof, only the division of the above functional modules is used as an example, in practical application, the above functional allocation may be implemented by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to implement all or part of the functions described above. In addition, the embodiments of the apparatus and the method provided in the foregoing embodiments belong to the same concept, and specific implementation processes of the embodiments of the method are detailed in the method embodiments, which are not repeated herein.
The application also discloses electronic equipment. Referring to fig. 3, fig. 3 is a schematic structural diagram of an electronic device according to the disclosure in an embodiment of the present application. The electronic device 500 may include: at least one processor 501, at least one network interface 504, a user interface 503, a memory 502, at least one communication bus 506.
Wherein the communication bus 506 is used to enable connected communication between these components.
The user interface 503 may include a Display screen (Display) and a Camera (Camera), and the optional user interface 503 may further include a standard wired interface and a standard wireless interface.
The network interface 504 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.
Wherein the processor 501 may include one or more processing cores. The processor 501 utilizes various interfaces and lines to connect various portions of the overall server, perform various functions of the server and process data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 502, and invoking data stored in the memory 502. Alternatively, the processor 501 may be implemented in hardware in at least one of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), programmable logic array (Programmable Logic Array, PLA). The processor 501 may integrate one or a combination of several of a central processing unit (Central Processing Unit, CPU), an image processor (Graphics Processing Unit, GPU), and a modem, etc. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 501 and may be implemented by a single chip.
The Memory 502 may include a random access Memory (Random Access Memory, RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 502 includes a non-transitory computer readable medium (non-transitory computer-readable storage medium). Memory 502 may be used to store instructions, programs, code sets, or instruction sets. The memory 502 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-described various method embodiments, etc.; the storage data area may store data or the like involved in the above respective method embodiments. The memory 502 may also optionally be at least one storage device located remotely from the processor 501. Referring to fig. 3, an operating system, a network communication module, a user interface module, and an application program of an inventory management method of a short shelf life commodity may be included in a memory 502 as a computer storage medium.
In the electronic device 500 shown in fig. 3, the user interface 503 is mainly used for providing an input interface for a user, and acquiring data input by the user; and the processor 501 may be configured to invoke an application in the memory 502 that stores an inventory management method for short shelf life merchandise, which when executed by the one or more processors 501, causes the electronic device 500 to perform the method as in one or more of the embodiments described above. It should be noted that, for simplicity of description, the foregoing method embodiments are all expressed as a series of action combinations, but it should be understood by those skilled in the art that the present application is not limited by the order of actions described, as some steps may be performed in other order or simultaneously in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required in the present application.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.
In the several embodiments provided herein, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, such as a division of units, merely a division of logic functions, and there may be additional divisions in actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some service interface, device or unit indirect coupling or communication connection, electrical or otherwise.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone goods, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution, in the form of a software product stored in a memory, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of the embodiments of the present application. And the aforementioned memory includes: various media capable of storing program codes, such as a U disk, a mobile hard disk, a magnetic disk or an optical disk.
The above are merely exemplary embodiments of the present disclosure and are not intended to limit the scope of the present disclosure. That is, equivalent changes and modifications are contemplated by the teachings of this disclosure, which fall within the scope of the present disclosure. Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure.
This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a scope and spirit of the disclosure being indicated by the claims.
Claims (10)
1. A method for inventory management of short shelf life commodities, applied to a server, comprising:
acquiring inventory management information of all warehouse commodities, wherein the inventory management information comprises inventory lists, historical sales lists, current quality guarantee remaining duration and position information of all commodities;
generating commodity demand of each warehouse in a future preset time period based on the historical sales list of each warehouse;
generating expected turnover quantity of each warehouse for various commodities based on inventory of various commodities and commodity demand in a future preset time period;
determining the actual turnover number of each warehouse for various commodities based on the current quality guarantee remaining time and the position information of the current various commodities;
and generating an inventory turnover list of each warehouse for each commodity based on the actual turnover number of each warehouse for each commodity, and sending the inventory turnover list to a mobile terminal of a warehouse manager.
2. The method for inventory management of short shelf life commodity according to claim 1, wherein said generating commodity demand in each warehouse for a predetermined time period in the future based on said historical sales listing of each warehouse comprises:
acquiring a first historical sales list of each warehouse in a recent preset time period;
acquiring a second historical sales list of each warehouse in a plurality of continuous histories within the same preset time period;
and generating commodity demand of each warehouse in a future preset time period according to the preset weight proportion based on the first historical sales list and the second historical sales list of each warehouse.
3. The method for inventory management of short shelf life commodity according to claim 2, wherein said step of generating commodity demand in future preset time period for each warehouse based on the first and second historical sales listings of each warehouse according to preset weight ratios comprises:
acquiring holiday information of a preset time period in the future;
acquiring a third historical sales list of each warehouse corresponding to the holiday of the past year;
generating a holiday commodity demand list of each warehouse in a future preset time period based on the third historical sales list;
And correcting the commodity demand of each warehouse in a future preset time period based on the holiday commodity demand list of each warehouse.
4. The method for inventory management of short shelf life commodities according to claim 1, wherein said determining the actual turnover number of each warehouse for each commodity based on the current shelf life remaining time and the position information of the current commodity comprises: acquiring maximum quality guarantee time, maximum net profit value, storage cost information and turnover cost information of the commodity;
generating a proportionality coefficient based on the current quality guarantee remaining time and the maximum quality guarantee time of the commodity; the proportionality coefficient is the ratio of the current quality guarantee remaining time length to the maximum quality guarantee time length;
generating a net profit value for the commodity based on the scaling factor of the commodity, the stored cost information and the maximum net profit value;
obtaining a commodity transfer quantity correction value based on the net profit value, turnover cost information and position information of the commodity and a preset commodity transfer correction function, wherein the commodity transfer correction function meets the following formula:
f(a,b,c)＝g(a)+h(b)*y(c)
wherein a, b, c are net profit value, turnover cost information and location information factors, respectively; g (a) is a maximum net profit value correction function, h (b) is a turnover cost information correction function, and y (c) is a position information correction function;
And determining the actual turnover quantity of each warehouse for various commodities based on the commodity transfer quantity correction value.
5. The method of claim 4, wherein the step of generating a net profit value for the commodity based on the commodity scaling factor, the storage cost information, and the maximum net profit value comprises:
generating a profit value for the commodity based on the product of the scaling factor and the maximum net profit value;
generating a cost value for the commodity based on the stored cost information;
judging whether the profit value of the commodity is larger than the cost value of the commodity, and if the profit value of the commodity is larger than the cost value of the commodity, generating a net profit value of the commodity; if the profit value of the commodity is not greater than the cost value of the commodity, the net profit value of the commodity is not generated.
6. The method of claim 4, wherein the step of determining the actual turnover number of each warehouse for each type of commodity based on the commodity transfer correction value comprises:
judging whether the numerical value of the commodity transfer correction function is larger than a preset threshold value or not;
if the numerical value of the commodity transferring correction function is larger than a preset threshold value, the actual turnover number of the commodity is reduced;
And if the numerical value of the commodity transferring correction function is not greater than the preset threshold value, transferring the commodity.
7. The method for inventory management of short shelf life commodity according to claim 4, wherein said step of determining the actual turnover number of each warehouse for each type of commodity based on the commodity transfer correction value comprises:
based on the current quality guarantee remaining time of the commodities, correcting the actual turnover quantity of each warehouse for various commodities;
and if the current quality guarantee remaining duration of the commodity is smaller than the preset time threshold, preferentially matching the commodity into a warehouse with large corresponding commodity demand.
8. A system for inventory management of short shelf life goods, the system comprising:
the acquisition module (11) is used for acquiring inventory management information of all warehouse commodities, wherein the inventory management information comprises inventory lists, historical sales lists, current quality guarantee remaining duration and position information of all types of commodities;
the processing module (12) is used for generating commodity demand of each warehouse in a future preset time period based on the historical sales list of commodities in each warehouse;
the processing module (12) is also used for generating the expected turnover number of each warehouse for various commodities based on the inventory of various commodities and the commodity demand in a preset time period in the future;
The processing module (12) is also used for acquiring the current quality guarantee remaining duration and position information of the commodities in each warehouse and determining the actual turnover number of the commodities in each warehouse;
the processing module (12) is also used for generating an inventory turnover list of each warehouse for various commodities based on the actual turnover quantity of each warehouse for various commodities;
and the sending module (13) is used for sending the inventory turnover list to the mobile terminal of the warehouse manager.
9. An electronic device comprising a processor (501), a memory (505), a user interface (503) and a network interface (504), the memory (505) being configured to store instructions, the user interface (503) and the network interface (504) being configured to communicate to other devices, the processor (501) being configured to execute the instructions stored in the memory (505) to cause the electronic device (500) to perform the method according to any of claims 1-7.
10. A computer readable storage medium storing instructions which, when executed, perform the method steps of any of claims 1-7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116823323A (en) * | 2023-08-28 | 2023-09-29 | 青岛场外市场清算中心有限公司 | Intelligent management method and system for market clearing data |
| CN117057760A (en) * | 2023-10-13 | 2023-11-14 | 深圳新语网络科技有限公司 | Enterprise catering management method and system based on small program |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116823323A (en) * | 2023-08-28 | 2023-09-29 | 青岛场外市场清算中心有限公司 | Intelligent management method and system for market clearing data |
| CN117057760A (en) * | 2023-10-13 | 2023-11-14 | 深圳新语网络科技有限公司 | Enterprise catering management method and system based on small program |
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