CN112036631B

CN112036631B - Purchasing quantity determining method, purchasing quantity determining device, purchasing quantity determining equipment and storage medium

Info

Publication number: CN112036631B
Application number: CN202010866307.5A
Authority: CN
Inventors: 杨粤
Original assignee: Guangzhou Shiyuan Electronics Thecnology Co Ltd
Current assignee: Guangzhou Shiyuan Electronics Thecnology Co Ltd
Priority date: 2020-08-25
Filing date: 2020-08-25
Publication date: 2024-06-18
Anticipated expiration: 2040-08-25
Also published as: CN112036631A

Abstract

The invention discloses a purchase quantity determining method, a device, equipment and a storage medium. Therefore, the purchasing quantity can be determined according to the material demand data in a certain time and MOQ strategies in various scenes, the ordering mode of ordering the next material purchasing order in one customized product order in the customized products is avoided, the time and labor cost of the purchasing party are reduced, the production cost and the transportation cost of the supplier are reduced, and the cooperation satisfaction degree of the two parties is improved.

Description

Purchasing quantity determining method, purchasing quantity determining device, purchasing quantity determining equipment and storage medium

Technical Field

The embodiment of the invention relates to the technical field of material purchasing, in particular to a purchasing quantity determining method, device, equipment and storage medium.

Background

Purchase quantity prediction is an important component in modern enterprises. The producer needs to determine the materials to be purchased, the purchasing period and the purchasing quantity according to the data of the stock, the cost and the like. In enterprise practice, the minimum purchase amount is determined by the suppliers according to the sum of the generation cost and the transportation cost, and is determined together with the purchasing party and is kept unchanged in a short period of time.

There is a special business model in existing enterprises that fully customizes the product. For fully customized products, the demand features are scattered and variable in quantity, the production and transportation costs are high for suppliers, and the inventory risk is high for purchasing parties. Thus, in particular practice, the purchasing party typically employs a means to customize the next purchase order of the product order, regardless of the quantity of demand.

In this way, the purchasing party needs to place purchasing orders for many times, the time and labor cost are increased, the production cost and the transportation cost of the suppliers are increased, and the cooperation satisfaction degree of the two parties is reduced.

Disclosure of Invention

The embodiment of the invention provides a purchasing quantity determining method, a purchasing quantity determining device, purchasing quantity determining equipment and a purchasing quantity determining storage medium, which are used for reducing the time and labor cost of a purchasing party, reducing the production cost and transportation cost of a supplier goose and improving the matching satisfaction degree of the two parties.

In a first aspect, an embodiment of the present invention provides a purchase quantity determining method, including:

Acquiring material demand data in a preset time period;

determining a demand scenario based on the material demand data;

Determining purchasing indexes under various minimum order quantity (Minimum Order Quantity, MOQ for short) strategies aiming at each demand scene;

And determining a target purchase amount based on the purchase indexes under all the demand scenes.

Further, the determining a plurality of demand scenarios based on the material demand data includes:

determining a data appearance rule based on the material demand data;

and generating a demand scene based on the data occurrence rule.

Further, the material demand data includes: material coding and demand quantity;

correspondingly, determining the data appearance rule based on the material demand data comprises the following steps:

determining the occurrence frequency rule of the material codes in the preset time period;

And determining the numerical rule of the required quantity corresponding to the material codes in the preset time period.

Further, generating a demand scenario based on the data occurrence rule includes:

determining a new demand date corresponding to the material code from the frequency rule;

and selecting the required quantity corresponding to the material codes from the numerical rule, and generating a required scene related to the newly-increased required date and the required quantity.

Further, determining purchase metrics under various minimum order quantity MOQ policies includes:

Calculating the total purchasing times and the total newly-added demand times under various MOQ strategies;

And determining the purchase times required by the newly-increased demand based on the purchase total times and the newly-increased demand total times.

Further, determining a target purchase amount based on the purchase index under all the demand scenarios includes:

and determining the purchasing quantity of which the purchasing times required by the newly added demand is greater than the preset purchasing times as a target purchasing quantity.

calculating total inventory and total newly added demand under various MOQ strategies;

and determining the inventory turnover days based on the total inventory and the total newly added demand.

and determining the purchasing quantity with the ratio of the total purchasing times to the purchasing times required by the newly added demand being larger than a preset value as a target purchasing quantity.

In a second aspect, an embodiment of the present invention further provides a purchase amount determining apparatus, including:

the data acquisition module is used for acquiring material demand data in a preset time period;

the scene determining module is used for determining a demand scene based on the material demand data;

the purchasing index determining module is used for determining purchasing indexes under various minimum order quantity MOQ strategies aiming at each demand scene;

And the purchase quantity determining module is used for determining a target purchase quantity based on the purchase indexes in all the demand scenes.

Further, the scene determination module includes:

the rule determining unit is used for determining a data appearance rule based on the material demand data;

And the scene generating unit is used for generating a demand scene based on the data occurrence rule.

Correspondingly, the rule determining unit is specifically configured to determine a frequency rule of occurrence of the material code in the preset time period; and determining the numerical rule of the required quantity corresponding to the material codes in the preset time period.

Further, the scene generating unit is specifically configured to determine a new added demand date corresponding to the material code from the frequency rule;

Further, the purchasing index determining module is specifically configured to calculate the total purchasing times and the total newly added demand times under various MOQ policies; and determining the purchase times required by the newly-increased demand based on the purchase total times and the newly-increased demand total times.

Further, the purchase quantity determining module is specifically configured to determine, as the target purchase quantity, a purchase quantity with the number of times of the new added demand being greater than a preset number of times of the new added demand.

Further, the purchasing index determining module is specifically used for calculating total inventory and total newly-increased demand under various MOQ strategies; and determining the inventory turnover days based on the total inventory and the total newly added demand.

Further, the purchase amount determining module is specifically configured to determine, as the target purchase amount, a purchase amount with the inventory turnover number of days being less than a preset number of days.

In a third aspect, an embodiment of the present invention further provides an apparatus, including:

One or more processors;

a memory for storing one or more programs;

The one or more programs are executed by the one or more processors, so that the one or more processors implement the purchase amount determining method provided in the first aspect of the embodiment of the invention.

In a fourth aspect, an embodiment of the present invention provides a computer readable storage medium having stored thereon one or more computer programs which when executed by a processor implement a purchase amount determining method as provided in the embodiment of the first aspect described above.

In the purchase quantity determining method, the device, the equipment and the storage medium, material demand data in a preset time period are firstly obtained, then demand scenes are determined based on the material demand data, then purchase indexes under various minimum order quantity MOQ strategies are determined for each demand scene, and finally target purchase quantity is determined based on the purchase indexes under all the demand scenes. Therefore, the purchasing quantity can be determined according to the material demand data in a certain time and MOQ strategies in various scenes, the ordering mode of ordering the next material purchasing order in one customized product order in the customized products is avoided, the time and labor cost of the purchasing party are reduced, the production cost and the transportation cost of the supplier are reduced, and the cooperation satisfaction degree of the two parties is improved.

Drawings

FIG. 1 is a flow chart of a method for determining an order quantity according to a first embodiment of the present invention;

FIG. 2 is a diagram showing a convergence curve of the purchase quantity according to the present embodiment;

FIG. 3 is a flowchart of a method for determining an order quantity according to a second embodiment of the present invention;

fig. 4 is a block diagram of an article recommendation device according to a third embodiment of the present invention;

fig. 5 is a schematic hardware structure of a device according to a fourth embodiment of the present invention.

Detailed Description

The invention is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting thereof. It should be further noted that, for convenience of description, only some, but not all of the structures related to the present invention are shown in the drawings.

Example 1

Fig. 1 is a flowchart of a method for determining a purchase amount according to an embodiment of the present invention, where the method is applicable to a case where a purchasing party or a supplier determines a minimum purchase amount of a material, the method may be performed by a purchase amount determining apparatus, and the apparatus may be implemented by hardware and/or software. The purchase amount determining means may be constituted by two or more physical entities or by one physical entity and is generally integrated in the computer device.

It should be noted that the method provided in this embodiment may be specifically used on a computer device, and may be considered to be specifically executed by a purchase amount determining apparatus integrated on the computer device, where the computer device may specifically be a computer device including a processor, a memory, an input apparatus, and an output apparatus. Such as notebook computers, desktop computers, tablet computers, intelligent terminals, and the like.

Specifically, the computer device can input the purchasing amount determining instruction input by the user through the input device in real time under the normal working state, analyze the material demand data, determine the target purchasing amount, and display the target purchasing amount to the user through the output device. Further, the input device may be an input device built into a computer device, such as: touch display screen, built-in voice input device, etc.; or an external input device connected with the computer device through a communication wire, such as: a mouse, a keyboard, etc. Further, the output device may be an output device built in a computer device, such as: touch display screens, etc.; or an external output device connected with the computer device through a communication line, such as: projectors, digital TVs, etc.

Specifically, as shown in fig. 1, the purchase amount determining method provided in the first embodiment of the present invention specifically includes the following operations:

s11, acquiring material demand data in a preset time period.

In this embodiment, the preset time period refers to a certain time interval, and the preset time period may be a specific time interval such as one week, two weeks, or one month. The correlation between the data with too long interval time and the future demand data is relatively weak, and the preset time period may be selected as a time interval closest to the specific current time. In addition, if the customized product has a certain time attribute, that is, the customized product is specifically used only in a certain period of time in one year, the preset time period can select the material demand data in the same time period in the previous year. For example, if the customized product is a mosquito net, since the mosquito net may have significantly increased demand in summer, it is not appropriate to acquire the time interval closest to the current time, and material demand data in the same time interval of the last year may be acquired. The preset time period may be determined according to the historical order quantity of the customized product and the attribute of the customized product, and is described in this embodiment, but is not limited thereto.

The material demand data refers to the newly increased demand quantity of the material A in a certain day. Wherein, the material demand data at least includes demand date, material code and demand quantity. It should be noted that, the required number in this embodiment refers to the number of newly increased required numbers in one day. The material code can be an identification for identifying a certain material, a specific name of the material or a string of digital codes. In this embodiment, for convenience of statistics, the material codes are a string of digital codes. The material demand data is exemplified by: 4.2 2010, material code is 004.001.123456x, newly increased demand number is 20000, 4.3 2010, material code is 004.001.123456z, and newly increased demand number is 2500. Table 1 is a material demand data table of a certain enterprise provided in this embodiment.

TABLE 1

Date of day	Material coding	Demand quantity
			2010-04-02	004.001.123456x	20000
2010-04-02	004.001.123456y	30
			2010-04-03	004.001.123456x	70
2010-04-03	004.001.123456z	2500
			2010-04-05	004.001.123456z	800

In this embodiment, acquiring material demand data within a preset time period acquires material demand data input by a user through an input device. The material demand data calculated in the MRP system can also be read from a database. Specifically, in this embodiment, acquiring the material demand data in the preset time period refers to reading daily material demand data calculated in the MRP system from the database.

Specifically, the reading of the material demand data calculated in the MRP system from the database may be reading the current day material demand data calculated in the MRP system from the database at a fixed time every day, then storing the current day material demand data, and reading the material demand data in a preset time period in the local storage. Or the material demand data in the operation preset time period in the MRP system can be directly read from the database. In this embodiment, only the method of acquiring the material demand data is described, but not limited thereto.

It should be noted that, the time of occurrence of the newly added material demand data is not determined, the time interval is also not determined, and the demand quantity is also not determined.

S12, determining a demand scene based on the material demand data.

In this embodiment, the number of occurrences of a material code and any required number of the material codes within a predetermined period of time are referred to as a required scenario. The occurrence times refer to the number of days of newly-increased material demand in a preset time period. For example: the material code is 004.001.123456x, the occurrence number is 10, and the number of occurrences corresponds to 2500 of a demand number, so that a demand scene is formed. The material code is 004.001.123456x, the occurrence number is 20, and the number corresponds to 200 of one demand, so that another demand scene is formed.

In this embodiment, in order to facilitate calculation of the number of occurrences of material codes, 0 may be filled in the required number corresponding to the date without requirement in the preset time.

Table 2 is a filled materials demand data table.

TABLE 2

In this embodiment, the number of days that the material coded as 004.001.123456x appears, and any required number of the material are obtained from the above table, and a required scene is obtained. In turn, for example, different demand numbers are obtained in turn, and different demand numbers appear.

S13, determining purchasing indexes under various MOQ strategies according to each demand scene.

In this embodiment, the minimum order quantity refers to the minimum production or shipment that the supplier is willing to afford when placing a single order to the supplier. The MOQ strategy refers to a decision scheme that calculates the minimum order quantity. In this embodiment, the MOQ policy is not limited, and any MOQ policy may be selected as the MOQ policy in this embodiment.

Further, multiple MOQ strategies may also be tried depending on the settings. For example: setting the MOQ last 100, max 2000, step 50, the moq= 100,150,200 … … up to 2000 will be tried, the impact and result for a certain random environment.

The purchase index is a parameter that determines a target purchase amount. The purchasing index in this embodiment includes, but is not limited to, the number of purchases required for the newly added demand and the number of days of inventory turnover. The number of times of purchasing needed by the newly added demand is determined by the total number of times of purchasing and the total number of times of the newly added demand. Inventory turnover number of days is determined by average inventory number of days, total number of days and total amount of newly added demand.

It should be noted that, the purchasing index under various MOQ strategies can be determined by adopting a material demand planning (Material Requirement Planning, MRP) system for calculation, and the purchasing index can be obtained only by inputting the data corresponding to the demand scene into the MRP system. The specific calculation method is not limited in this embodiment.

S14, determining a target purchase quantity based on the purchase indexes in all the demand scenes.

In this embodiment, the target purchase amount refers to the minimum production amount or shipment amount that the provider is willing to afford. The target purchase amount can be determined according to the number of purchases required by the newly added demand and the number of days of inventory turnover.

Furthermore, quantitative analysis can be performed on purchasing indexes under various demand scenes, and the target purchasing quantity is determined according to the convergence position of the curve.

Fig. 2 is a diagram of a purchase amount convergence curve according to the present embodiment. And forming a curve shown in fig. 2 based on purchase indexes under different MOQ strategies in all demand scenes, and determining the target purchase quantity according to the convergence of the curve. And determining the abscissa corresponding to the convergence point of the curve as the target purchase quantity.

According to the item recommending method provided by the embodiment of the invention, firstly, material demand data in a preset time period is acquired, then, demand scenes are determined based on the material demand data, then, purchasing indexes under various minimum order quantity MOQ strategies are determined for each demand scene, and finally, target purchasing quantity is determined based on purchasing indexes under all the demand scenes. Therefore, the purchasing quantity can be determined according to the material demand data in a certain time and MOQ strategies in various scenes, the ordering mode of ordering the next material purchasing order in one customized product order in the customized products is avoided, the time and labor cost of the purchasing party are reduced, the production cost and the transportation cost of suppliers are reduced, and the cooperation satisfaction degree of the two parties is improved.

Example two

Fig. 3 is a schematic flow chart of a purchasing amount determining method according to a second embodiment of the present invention, where optimization is performed based on the second embodiment, and in this embodiment, determining a data occurrence rule based on the material demand data is further optimized to determine a frequency rule of occurrence of the material codes in the preset time period; and determining the numerical rule of the required quantity corresponding to the material codes in the preset time period. And generating a demand scene based on the data occurrence rule, optimizing to select the times corresponding to one material code from the times rule, selecting the numerical value corresponding to the material code from the numerical value rule, and generating the demand scene corresponding to the material code.

As shown in fig. 3, the article recommending method provided in the second embodiment of the present invention specifically includes the following operations:

s21, acquiring material demand data in a preset time period.

S22, determining the occurrence frequency rule of the material codes in the preset time period.

In this embodiment, the occurrence frequency rule of the material codes may be understood as a digital rule according with the number of days of newly increasing the material demand in a preset time period.

In this embodiment, three methods for determining occurrence frequency rules of material codes are provided: based on bernoulli distribution, based on poisson distribution, based on markov chains.

1. And determining the occurrence frequency rule of the material codes based on the Bernoulli distribution.

And in a preset time period, the ratio of the number of occurrence times of material codes to the total number of days is the parameter p of Bernoulli distribution. The parameter p is the occurrence frequency rule of the material codes.

For example: for a total of 22 workdays for 4 months, 8 demands were made of material coded 004.001.123456x, the parameter p=0.363.

The Bernoulli distribution is adopted to determine the occurrence frequency rule of the material codes, so that the requirement scene is determined.

2. And determining the occurrence frequency rule of material codes based on poisson distribution.

And in a plurality of equivalent time spans, the average number of times of occurrence of new material demand is the value of the parameter k of the poisson distribution. The time span includes, but is not limited to, weeks, months, and quarters.

In this example, a month is taken as an example. For example: the number of times of material with the material code of 004.001.123456x appears in 1 month, 2 months and 3 months is 4 times, 9 times and 5 times respectively, the average number of times of occurrence in each month is 6 times, and the value of the parameter k of poisson distribution is 6.

The code occurrence rule of the material is determined based on the poisson distribution, and the total number of the requirement occurrence in one period is regarded as approximate normal distribution, rather than considering the probability of each requirement occurrence like the Bernoulli distribution.

3. And determining the occurrence frequency rule of the material codes based on the Markov chain.

And counting the occurrence times of the four types of events in a preset time period, and dividing the occurrence times of the four types of events by the total occurrence times to obtain the occurrence probability of each state. Four types of events are [ there is a need- > there is no need ], there is a need- > there is a need ] [ there is no need- > there is no need ] [ there is no need- > there is a need ]. Wherein, there is a new demand on the previous day indicated by the expression "there is a demand" > there is no new demand on the current day ". For example: material A is required for 1 month and no requirement for 2 months, and the requirement is represented by [ with requirement- > no requirement ]. In the same way, the expression of [ there is a demand- > there is a demand ] indicates that there is a new demand on the previous day and there is a new demand on the current day. No demand- > no demand ] indicates that there is no new demand on the previous day, and there is no new demand on the current day. No demand- > there is a demand for new increase on the day, which indicates that there is no demand for new increase on the day.

And a Markov chain is adopted to determine the occurrence frequency rule of material codes, so that the influence of the demand state on the current day before is considered, and the demand scene is determined.

For example: as in the example above, for material coded 004.001.123456 x. There are the requirements shown in table 3.

TABLE 3 Table 3

The state transition count matrix shown in table 4 can be obtained by the transition:

TABLE 4 Table 4

State (row: original state, column: new state)	No need exists	There is a need for
			No need exists	3	3
There is a need for	2	1

The value in each row is divided by the sum of the rows to obtain the state transition probability matrix shown in table 5.

TABLE 5

State (row: original state, column: new state)	No need exists	There is a need for
			No need exists	50％	50％
There is a need for	67％	32％

S23, determining a numerical rule of the required quantity corresponding to the material codes in the preset time period.

In this embodiment, the numerical rule of the required quantity corresponding to the material code refers to a numerical rule that the newly added material required quantity accords with in a preset time period.

In the present embodiment, two methods are provided to determine the numerical rule of the required number: based on beta distribution, based on kernel density Estimation (KERNEL DENSITY Estimation, KDE).

1. The numerical law of the number of demands is determined based on the beta distribution.

Beta you and the distribution rule are used according to the size of the number of the demands. The specific parameters of a specific beta fit may be implemented by computer software, which is not specifically described in this embodiment.

The advantage of determining the numerical law of the number of demands based on the beta distribution is easy understanding.

2. And determining the numerical rule of the required quantity based on the KDE.

And selecting proper kernels and bandwidths according to the data characteristics of the required quantity, and fitting a distribution rule by using a KDE. The specific parameters of a specific KDE fit may be implemented by computer software, which is not specifically described in this embodiment.

And determining the numerical rule of the required quantity based on the KDE, and after selecting a proper KDE core, well processing the multimodal data distribution.

S24, determining a new demand date corresponding to the material code from the frequency law.

In this embodiment, based on the extracted occurrence rule, a new demand date is generated.

1. Bernoulli distribution: for each date, the p-value of the parameter of a product is used, and whether the demand exists or not is randomly generated.

2. Poisson distribution: for a selected period, based on the k value of each material, the eating of the demand occurring in that period is generated, and for that number, randomly assigned to a certain date in the period.

3. Markov chain: and giving that the initial state is free of requirements, and generating random results according to the state transition probability matrix sequentially every day.

For example: the initial state is no-demand, 2020-04-01 randomizes demand as a result according to the probability of [ no-demand- > no-demand ], no-demand- > demand. 2020-04-02 randomly calculates the no-need as a result based on the probability of [ having a need- > no-need ], [ having a need- > no-need ]. And by analogy, determining whether each date has a new requirement or not.

S25, selecting the required quantity corresponding to the material codes from the numerical rule, and generating a required scene related to the newly-added required date and the required quantity.

And sampling corresponding times from the corresponding distribution according to the extracted numerical rule and the corresponding times of each material, and distributing the times to the new demand date determined in the step S24 to form final new demand data.

For example: from the above, it can be seen that the demand occurs for a total of 7 days, and then 7 points are randomly extracted in the beta distribution and then randomly allocated to the 7 days, so as to form the final newly increased demand number, as shown in table 6.

TABLE 6

S26, determining purchasing indexes under various minimum order quantity MOQ strategies according to each demand scene.

For each demand scenario, a different MOQ strategy is tried. For the demand scenario described in table 6, the strategy of moq=100 was used for all 3 materials, resulting in the data shown in table 7.

TABLE 7

Wherein the determining purchase index under various minimum order quantity MOQ strategies comprises: calculating the total purchasing times and the total newly-added demand times under various MOQ strategies; and determining the purchase times required by the newly-increased demand based on the purchase total times and the newly-increased demand total times.

Specifically, the number of purchases required by the newly added demand is the ratio of the total number of purchases to the total number of purchases required by the newly added demand.

Further, determining purchase metrics under various minimum order quantity MOQ policies includes: calculating total inventory and total newly added demand under various MOQ strategies; and determining the inventory turnover days based on the total inventory and the total newly added demand.

Wherein the total inventory is the product of the daily average inventory and the total days. Inventory turnover number of days refers to the ratio of total inventory to total demand.

S27, determining a target purchase quantity based on purchase indexes in all the demand scenes.

In this embodiment, two ways of determining the target purchase amount are provided:

One way is: and determining the purchasing quantity with the inventory turnover number of days smaller than the preset number of days as a target purchasing quantity.

For example: and determining a material code corresponding to the date in the demand scene corresponding to the MOQ strategy with the turnover number of days being less than or equal to N days and a corresponding newly-increased demand number as a target purchase amount.

Another way is: and determining the purchasing quantity with the ratio of the total purchasing times to the purchasing times required by the newly added demand being larger than a preset value as a target purchasing quantity.

For example: and determining a material code corresponding to the date in a demand scene corresponding to the MOQ strategy with the ratio of the total purchasing times to the purchasing times required by the newly added demand being larger than the preset percentage and the corresponding newly added demand quantity as a target purchasing quantity.

According to the item recommending method provided by the embodiment of the invention, firstly, material demand data in a preset time period is obtained, a frequency rule of occurrence of material codes in the preset time period is determined, a numerical rule of demand quantity corresponding to the material codes is selected from the frequency rule, the number corresponding to the material codes is selected from the numerical rule, a demand scene corresponding to the material codes is generated, then purchasing indexes under various minimum order quantity MOQ strategies are determined for each demand scene, and finally, target purchasing quantity is determined based on purchasing indexes under all demand scenes. Therefore, the purchasing quantity can be determined according to the material demand data in a certain time and MOQ strategies in various scenes, the ordering mode of ordering the next material purchasing order in one customized product order in the customized products is avoided, the time and labor cost of the purchasing party are reduced, the production cost and the transportation cost of suppliers are reduced, and the cooperation satisfaction degree of the two parties is improved.

Example III

Fig. 4 is a block diagram of a purchase amount determining apparatus according to a third embodiment of the present invention. The purchase quantity determining means are suitable for use in the case where the purchasing party or the supplier determines a minimum order quantity for the material, and the purchase quantity determining means may be implemented in hardware and/or software and are typically integrated in the smart device. As shown in fig. 4, the apparatus includes: a data acquisition module 401, a scene determination module 402, a purchase index determination module 403, and a purchase quantity determination module 404.

The data acquisition module 401 is configured to acquire material demand data in a preset time period;

A scene determination module 402, configured to determine a demand scene based on the material demand data;

A purchasing index determining module 403, configured to determine purchasing indexes under various minimum order quantity MOQ policies for each demand scenario;

And the purchase quantity determining module 404 is configured to determine a target purchase quantity based on the purchase indexes in all the demand scenarios.

In this embodiment, the device first obtains material demand data in a preset time period, then determines demand scenes based on the material demand data, then determines purchasing indexes under various minimum order quantity MOQ policies for each demand scene, and finally determines a target purchasing quantity based on purchasing indexes under all demand scenes. Therefore, the purchasing quantity can be determined according to the material demand data in a certain time and MOQ strategies in various scenes, the ordering mode of ordering the next material purchasing order in one customized product order in the customized products is avoided, the time and labor cost of the purchasing party are reduced, the production cost and the transportation cost of a goose of a supplier are reduced, and the cooperation satisfaction degree of the two parties is improved.

Further, the scene determination module 402 includes:

Further, the purchase index determining module 403 is specifically configured to calculate the total number of purchases and the total number of newly added demands under various MOQ policies; and determining the purchase times required by the newly-increased demand based on the purchase total times and the newly-increased demand total times.

Further, the purchase amount determining module 404 is specifically configured to determine, as the target purchase amount, a purchase amount that the number of times of the new added demand is greater than the preset number of times of the new added demand.

Further, the purchasing index determining module 403 is specifically configured to calculate total inventory and total newly added demand under various MOQ policies; and determining the inventory turnover days based on the total inventory and the total newly added demand.

Further, the purchase amount determining module 404 is specifically configured to determine, as the target purchase amount, a purchase amount whose ratio of the total number of purchases to the number of purchases required by the newly added demand is greater than a preset value.

The purchasing quantity determining device provided by the embodiment of the invention can execute the purchasing quantity determining method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the executing method.

Example IV

Fig. 5 is a schematic hardware structure of an apparatus according to a fourth embodiment of the present invention, where, as shown in fig. 5, the apparatus includes a processor 501, a memory 502, an input device 503, and an output device 504; the number of processors 501 in the device may be one or more, one processor 501 being taken as an example in fig. 5; the processor 501, memory 502, input means 503 and output means 504 in the device may be connected by a bus or other means, in fig. 5 by way of example.

The memory 502 is used as a computer readable storage medium, and may be used to store a software program, a computer executable program, and modules, such as program instructions/modules corresponding to the purchase amount determining method in the embodiment of the present invention (for example, the modules in the purchase amount determining apparatus shown in fig. 4 include the data obtaining module 401, the scene determining module 402, the purchase index determining module 403, and the purchase amount determining module 404). The processor 501 executes various functional applications of the device and data processing by running software programs, instructions, and modules stored in the memory 502, i.e., implements the purchase amount determination method described above.

Memory 502 may include primarily a program storage area and a data storage area, wherein the program storage area may store an operating system, at least one application program required for functionality; the storage data area may store data created according to the use of the device, etc. In addition, memory 502 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device. In some examples, memory 502 may further include memory located remotely from processor 501, which may be connected to the device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

And, when one or more programs included in the above-described apparatus are executed by the one or more processors 501, the programs perform the following operations:

Acquiring material demand data in a preset time period;

determining a demand scenario based on the material demand data;

Determining purchasing indexes under various minimum order quantity MOQ strategies aiming at each demand scene;

The input means 503 may be used to receive entered numeric or character information and to generate key signal inputs related to user settings and function control of the device. The output 504 may include a display device such as a display screen.

Example five

The fifth embodiment of the present invention further provides a computer readable storage medium having stored thereon a computer program which, when executed by a processing device, implements the purchase amount determination method provided in the first or second embodiment of the present invention, the method including:

Acquiring material demand data in a preset time period;

determining a demand scenario based on the material demand data;

Of course, the storage medium containing the computer executable instructions provided in the embodiments of the present invention is not limited to the method operations described above, and may also perform the related operations in the purchase amount determination method provided in any embodiment of the present invention.

From the above description of embodiments, it will be clear to a person skilled in the art that the present invention may be implemented by means of software and necessary general purpose hardware, but of course also by means of hardware, although in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a FLASH Memory (FLASH), a hard disk, or an optical disk of a computer, etc., and include several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments of the present invention.

It should be noted that, in the embodiment of the purchase amount determining apparatus, each unit and module included are only divided according to the functional logic, but not limited to the above division, so long as the corresponding function can be implemented; in addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the present invention.

Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.

Claims

1. A purchase quantity determination method, comprising:

acquiring material demand data in a preset time period, wherein the preset time period comprises: the time interval of the closest current time or the last year of the current time;

determining a demand scenario based on the material demand data;

determining a target purchase quantity based on the purchase indexes under all the demand scenes;

Wherein the determining a plurality of demand scenarios based on the material demand data comprises:

determining a data appearance rule based on the material demand data;

generating a demand scene based on the data occurrence rule;

wherein the material demand data comprises: material coding and demand quantity;

Determining the occurrence frequency rule of the material codes within the preset time period, wherein the method for determining the occurrence frequency rule of the material codes comprises the following steps: based on Bernoulli distribution, based on Poisson distribution, or based on Markov chains;

determining a numerical rule of the required quantity corresponding to the material codes in the preset time period, wherein the method for determining the numerical rule of the required quantity comprises the following steps: based on beta distribution or based on kernel density estimation.

2. The purchase quantity determining method according to claim 1, wherein generating a demand scenario based on the data appearance rule includes:

3. The purchase quantity determining method of claim 1, wherein determining purchase metrics under various minimum order quantity MOQ policies includes:

4. The purchase quantity determining method according to claim 3, wherein determining a target purchase quantity based on the purchase index in all demand scenarios includes:

5. The purchase quantity determining method of claim 1, wherein determining purchase metrics under various minimum order quantity MOQ policies includes:

6. The purchase quantity determining method of claim 5, wherein determining a target purchase quantity based on the purchase index in all demand scenarios includes:

And determining the purchasing quantity with the inventory turnover number of days smaller than the preset number of days as a target purchasing quantity.

7. A purchase quantity determining apparatus, comprising:

the data acquisition module is used for acquiring material demand data in a preset time period, wherein the preset time period comprises: the time interval of the closest current time or the last year of the current time;

The purchasing quantity determining module is used for determining a target purchasing quantity based on the purchasing indexes in all the demand scenes;

wherein, scene determination module includes:

The scene generating unit is used for generating a demand scene based on the data occurrence rule;

Correspondingly, the rule determining unit is specifically configured to determine a frequency rule of occurrence of the material code in the preset time period, where the method for determining the frequency rule of occurrence of the material code includes: based on Bernoulli distribution, based on Poisson distribution, or based on Markov chains; determining a numerical rule of the required quantity corresponding to the material codes in the preset time period, wherein the method for determining the numerical rule of the required quantity comprises the following steps: based on beta distribution or based on kernel density estimation.

8. An electronic device, comprising:

One or more processors;

a memory for storing one or more programs;

the one or more programs are executed by the one or more processors to cause the one or more processors to implement the purchase quantity determination method of any of claims 1-6.

9. A computer-readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements a purchase quantity determination method as claimed in any of claims 1-6.