CN112036631A

CN112036631A - Purchasing quantity determination method, device, equipment and storage medium

Info

Publication number: CN112036631A
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: 2020-12-04

Abstract

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

Description

Purchasing quantity determination method, device, equipment and storage medium

Technical Field

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

Background

Procurement quantity forecast is an important component in modern enterprises. The production manufacturer needs to determine the material to be purchased, the purchasing period and the purchasing quantity according to various data such as inventory, cost and the like. In business practice, the minimum purchase amount is determined by the supplier and the purchasing party after being calculated according to the sum of the production cost and the transportation cost, and is kept unchanged in a short time.

A special business model exists in existing enterprises, namely fully customized products. For fully customized products, the characteristics of the demand are scattered and the quantity is variable, for suppliers, the production and transportation cost is high, and for purchasing parties, the inventory risk is high. Therefore, in particular practice, the purchasing party typically places a purchase order for a custom product order regardless of the quantity required.

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

Disclosure of Invention

The embodiment of the invention provides a method, a device, equipment and a storage medium for determining the purchasing quantity, which can be 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 of the purchasing party and the supplier goose.

In a first aspect, an embodiment of the present invention provides a method for determining a purchase amount, 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 (MOQ) strategies aiming at each demand scene;

and determining a target purchasing amount based on the purchasing indexes under all demand scenes.

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

determining a data occurrence 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 required quantity;

correspondingly, determining a data occurrence rule based on the material demand data comprises:

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

and determining a 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 newly added demand date corresponding to the material code from the frequency rule;

and selecting the required quantity corresponding to the material code from the numerical rule, and generating a required scene in which the newly added required date is associated with the required quantity.

Further, determining purchasing indexes under various minimum order quantity MOQ strategies comprises the following steps:

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

and determining the purchasing times required by the newly increased demand based on the total purchasing times and the total newly increased demand times.

Further, determining a target purchasing amount based on the purchasing indicators in all demand scenarios includes:

and determining the purchase quantity of which the purchase times required by the newly increased demand are greater than the preset purchase times as a target purchase quantity.

calculating the total inventory and the newly increased demand total under various MOQ strategies;

and determining the turnover days of the stock based on the total inventory and the total quantity of the newly added demands.

and determining the purchase quantity with the ratio of the total purchase times to the number of purchase times required by the newly increased demand larger than a preset value as the target purchase quantity.

In a second aspect, an embodiment of the present invention further provides a device for determining a purchase amount, 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 purchasing amount determining module is used for determining the target purchasing amount based on the purchasing indexes under all the demand scenes.

Further, the scene determination module includes:

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

and the scene generation 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 rule of the number of times of occurrence of the material codes within the preset time period; and determining a numerical rule of the required quantity corresponding to the material codes in the preset time period.

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

Further, the purchase index determining module is specifically used for calculating the total purchase times and the total newly added demand times under various MOQ strategies; and determining the purchasing times required by the newly increased demand based on the total purchasing times and the total newly increased demand times.

Further, the purchase quantity determining module is specifically configured to determine, as the target purchase quantity, the purchase quantity for which the number of times of purchasing required by the new demand is greater than a preset number of times of purchasing.

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

Further, the purchase quantity determining module is specifically configured to determine the purchase quantity with the inventory turnover days smaller than the preset days as the target purchase quantity.

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 to cause the one or more processors to implement the purchase amount determination method as provided above in the first aspect of the embodiment of the present invention.

In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which one or more computer programs are stored, and when the computer programs are executed by a processor, the method for determining the purchase amount provided in the above embodiment of the first aspect is implemented.

In the method, the device, the equipment and the storage medium for determining the purchase quantity, 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 purchase quantity can be determined according to the material demand data in a certain time and the MOQ strategies under various scenes, the ordering mode that one customized product order is used for ordering the next material purchase order in the customized product is avoided, the time and labor cost of a purchasing party are reduced, the production cost and the transportation cost of a supplying party are reduced, and the matching satisfaction of the purchasing party and the supplying party is improved.

Drawings

FIG. 1 is a flowchart of an order quantity determining method according to an embodiment of the present invention;

FIG. 2 is a diagram illustrating the convergence of the procurement amount provided by the embodiment;

FIG. 3 is a flowchart of an order quantity determining method 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 diagram of a hardware structure of an apparatus according to a fourth embodiment of the present invention.

Detailed Description

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

Example one

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 suitable for a buyer or a supplier to determine a minimum purchase amount of a material, and the method may be performed by a purchase amount determining apparatus, which may be implemented by hardware and/or software. The purchase amount determining device may be formed by two or more physical entities or may be formed by one physical entity, and is generally integrated into a 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 device, and an output device. Such as notebook computers, desktop computers, tablet computers, intelligent terminals, and the like.

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

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

and 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. Wherein, the preset time period may be selected as the time interval with the closest specific current time, because the relevance of the data with too long time interval and the future requirement data is relatively weak. In addition, if the customized product has a certain time attribute, that is, the customized product is only used specifically in a certain period of time in a year, the preset period of time may be selected from the material demand data in the period of time in the previous year. For example, if the customized product is a mosquito net, since the demand of the mosquito net in summer may be significantly increased, it is not appropriate to acquire the time interval closest to the current time, and the material demand data of the same time period in the last year can be acquired. The preset time period may be determined according to the historical order amount of the customized product and the attribute of the customized product, and the preset time period is further described in this embodiment, but is not limited thereto.

The material demand data refers to the newly added demand quantity of the material A in a certain day. The material demand data at least comprises a demand date, a material code and a demand quantity. It should be noted that the demand quantity in this embodiment refers to a demand quantity newly added in one day. The material code may be an identifier for identifying a certain material, a specific name of the material, or a string of numeric codes. In this embodiment, for convenience of statistics, the material code is a string of digital codes. Illustratively, the specific content of the material requirement data is as follows: 2 days 4 months in 2010, the material code is 004.001.123456 x's material, and newly-increased demand quantity is 20000, and 3 days 4 months in 2010, the material code is 004.001.123456 z's material, and newly-increased demand quantity is 2500. Table 1 is a material demand data table of a certain enterprise provided in this embodiment.

TABLE 1

Date	Material coding	Required 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, the material demand data within the preset time period is acquired, and the material demand data input by the user through the input device is acquired. Or reading the material demand data operated in the MRP system from the database. Specifically, in this embodiment, the obtaining of the material demand data within 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 operated in the MRP system from the database may be reading the material demand data operated in the MRP system on the same day from the database at a fixed time every day, storing the material demand data every day, and reading the material demand data in a preset time period in a local storage. Or, the material demand data in the preset time period of the operation in the MRP system can be directly read from the database. In the present embodiment, only the manner of acquiring the material demand data is described, but not limited thereto.

It should be noted that the time of the newly added material demand data is uncertain, the time interval is also uncertain, and the demand quantity is also uncertain.

And 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 preset time period are referred to as a required scene. The occurrence frequency refers to the number of days for newly adding materials in a preset time period. For example: the material code is 004.001.123456x, the occurrence frequency is 10 times, and a demand amount is 2500, so that a demand scene is formed. The material with the material code of 004.001.123456x appears 20 times and corresponds to a demand amount of 200 to form another demand scenario.

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

Table 2 is a table of filled material demand data.

TABLE 2

In this embodiment, the number of days that the material with the material code of 004.001.123456x appears and the required quantity of any one of the materials are obtained from the above table, and a required scene is obtained. For example, different required quantities are obtained in sequence, and different required quantities appear.

And 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 quantity or shipping quantity that the supplier is willing to undertake when placing an order for a pen from the supplier. The MOQ policy refers to a decision scheme for calculating a minimum amount of orders. In this embodiment, the MOQ policy is not limited, and any one of the MOQ policies 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 to last 100, max 2000, step 50, will try to get the MOQ 100,150,200 … … up to 2000, the impact and the result for a random environment.

The procurement index is a parameter for determining a target procurement amount. The procurement index in this embodiment includes, but is not limited to, the number of procurement required for the new demand and the number of turnover days of the stock. Wherein, the number of times of purchasing required by the newly increased demand is determined by the total number of times of purchasing and the total number of times of newly increased demand. The inventory turnover days are determined by the daily average inventory days, the total days and the total quantity of newly added demands.

It should be noted that the purchasing index under various MOQ policies can be calculated by using a Material Requirement Planning (MRP) system, and the purchasing index can be obtained only by inputting data corresponding to a Requirement scenario into the MRP system. The specific calculation method is not limited in this embodiment.

And S14, determining the target purchasing quantity based on the purchasing index under all the demand scenes.

In this embodiment, the target purchase amount refers to the minimum production amount or shipping amount that the supplier is willing to undertake. The target purchasing quantity can be determined according to the purchasing times and the inventory turnover days required by the newly increased demand.

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 the convergence of the procurement amount provided by the embodiment. A curve as shown in fig. 2 is formed based on the procurement indexes under different MOQ strategies under all demand scenarios, and the target procurement amount is determined according to the convergence of the curve. Namely, the abscissa corresponding to the convergence point of the curve is determined as the target purchase amount.

The article recommendation method provided by the embodiment of the invention includes the steps of firstly obtaining material demand data in a preset time period, then determining demand scenes based on the material demand data, then determining purchase indexes under various minimum order quantity MOQ strategies aiming at each demand scene, and finally determining target purchase quantity based on the purchase indexes under all the demand scenes. Therefore, the purchase quantity can be determined according to the material demand data in a certain time and the MOQ strategies under various scenes, the ordering mode that one customized product order is used for ordering the next material purchase order in the customized product is avoided, the time and labor cost of a purchasing party are reduced, the production cost and the transportation cost of a supplier are reduced, and the matching satisfaction of the purchasing party and the supplier is improved.

Example two

Fig. 3 is a schematic flow chart of a method for determining a purchase amount according to a second embodiment of the present invention, where the second embodiment is optimized based on the above-mentioned second embodiment, in this embodiment, a data occurrence rule based on the material demand data is further optimized to determine a rule of times of occurrence of the material codes within the preset time period; and determining a 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 the demand scene into times corresponding to a material code selected from the times rule, selecting a value corresponding to the material code from the value rule, and generating the demand scene corresponding to the material code.

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

and S21, acquiring material demand data in a preset time period.

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

In this embodiment, the material code occurrence frequency rule may be understood as a digital rule that the number of days for which the material needs to be newly added in a preset time period is consistent.

In this embodiment, three methods for determining the rule of occurrence times 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 Bernoulli distribution.

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

For example: there are 22 working days in month 4, where 8 demands for material with material code 004.001.123456x occurred, and parameter p is 0.363.

The Bernoulli distribution is adopted to determine the material code occurrence frequency rule, so that the requirement scene can be determined.

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

And in a plurality of equivalent time spans, the average frequency of the newly increased demands of a certain material is the parameter k value of the Poisson distribution. The time span includes, but is not limited to, week, month, quarter.

In the present embodiment, a month will be taken as an example for explanation. For example: the material with material code 004.001.123456x appears 4 times, 9 times and 5 times in 1 month, 2 months and 3 months respectively, so that the average number of occurrences in each month is 6 times, and the parameter k value of the Poisson distribution is 6.

And determining a material code occurrence frequency rule based on Poisson distribution, and regarding the total times of the occurrence of the demands in one period as approximate normal distribution instead of considering the probability of the occurrence of each demand like 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. The four types of events refer to [ with demand- > without demand ], and [ with demand- > with demand ] [ without demand- > without demand ] [ without demand- > with demand ]. Wherein [ with demand- > without demand ] indicates that the previous day has new demand and the current day has no new demand. For example: material A has a demand in 1 month 4, and has no demand in 2 months 4, and is represented by (having demand- > having no demand). By analogy, the previous day represented by [ having a demand- > having a demand ] has a new demand, and the current day has a new demand. [ No demand- > No demand ] indicates that no new demand exists in the previous day and no new demand exists in the same day. [ No demand- > with demand ] means that there is no new demand in the previous day and there is new demand in the same day.

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

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

TABLE 3

The state transition times matrix shown in table 4 can be obtained by conversion:

TABLE 4

State (line: original state, line: new state)	Without need	Has need of
			Without need	3	3
Has need of	2	1

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

TABLE 5

State (line: original state, line: new state)	Without need	Has need of
			Without need	50％	50％
Has need of	67％	32％

And S23, determining the 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 required quantity of the newly added material meets the requirement in a preset time period.

In this embodiment, two methods are provided to determine the numerical rule of the required quantity: based on beta distribution, based on Kernel Density Estimation (KDE).

1. And determining a numerical rule of the required quantity based on the beta distribution.

According to the size of the number of the appeared demands, beta you and a distribution rule are used. The specific parameters of the specific beta fitting can be implemented by computer software, and are not specifically described in this embodiment.

The numerical rule for determining the required quantity based on the beta distribution has the advantage of easy understanding.

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

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

The numerical rule of the required quantity is determined based on KDE, and multimodal data distribution can be well processed after a proper KDE core is selected.

And S24, determining the newly added requirement date corresponding to the material code from the frequency rule.

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

1. Bernoulli distribution: for each date, the presence or absence of demand is randomly generated using the value of the parameter p for a product.

2. Poisson distribution: for the selected period, according to the k value of each material, the eating with the demand in the period is generated, and the times are randomly assigned to a certain date in the period.

3. Markov chain: giving an initial state as a non-demand state, and sequentially generating random results according to the state transition probability matrix every next day.

For example: the initial state is not required, 2020-04-01 randomly finds out the requirement as the result according to the probability of [ not required- > not required ], and [ not required- > required ]. 2020-04-02 randomly finds out the needless-to-ask result according to the probability of [ having demand- > not asking ], and [ having demand- > not asking ]. And analogizing in turn, and determining whether each date has a new demand or not.

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

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

For example: as can be seen from the above, if there are 7 days of requests, then in the beta distribution, 7 points are randomly extracted and randomly allocated to the 7 days, so as to form the final number of newly added requests, as shown in Table 6.

TABLE 6

And 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 the purchasing indexes under various minimum order quantity MOQ strategies comprises the following steps: calculating the total purchasing times and the total newly added demand times under various MOQ strategies; and determining the purchasing times required by the newly increased demand based on the total purchasing times and the total newly increased demand times.

Specifically, the number of times of purchasing required by the newly added demand is a ratio of the total number of times of purchasing to the total number of times of the newly added demand.

Further, determining purchasing indexes under various minimum order quantity MOQ strategies comprises the following steps: calculating the total inventory and the newly increased demand total under various MOQ strategies; and determining the turnover days of the stock based on the total inventory and the total quantity of the newly added demands.

Wherein the total inventory is the product of the daily average inventory and the total number of days. The number of turnover days of the stock refers to the ratio of the total stock to the total amount of the newly added demand.

And S27, determining the target purchasing quantity based on the purchasing indexes under all the demand scenes.

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

one way is that: and determining the purchase quantity with the inventory turnover days smaller than the preset days as a target purchase quantity.

For example: and determining the material codes corresponding to the dates in the demand scenes corresponding to the MOQ strategies with the turnover days less than or equal to N days and the corresponding newly increased demand quantity as the target purchase quantity.

The other mode is as follows: and determining the purchase quantity with the ratio of the total purchase times to the number of purchase times required by the newly increased demand larger than a preset value as the target purchase quantity.

For example: and determining the material code corresponding to the date in the demand scene corresponding to the MOQ strategy in which the ratio of the total purchasing times to the purchasing times required by the newly increased demand is greater than the preset percentage and the number of the newly increased demand as the target purchasing quantity.

The article recommendation method provided by the embodiment of the invention comprises the steps of firstly obtaining material demand data in a preset time period, determining a frequency rule of occurrence of material codes and a numerical rule of demand quantity corresponding to the material codes in the preset time period, then selecting the frequency corresponding to one material code from the frequency rule, selecting a numerical value corresponding to the material code from the numerical rule, generating a demand scene corresponding to the material code, then determining purchase indexes under various minimum order quantity MOQ strategies aiming at each demand scene, and finally determining a target purchase quantity based on the purchase indexes under all the demand scenes. Therefore, the purchase quantity can be determined according to the material demand data in a certain time and the MOQ strategies under various scenes, the ordering mode that one customized product order is used for ordering the next material purchase order in the customized product is avoided, the time and labor cost of a purchasing party are reduced, the production cost and the transportation cost of a supplier are reduced, and the matching satisfaction of the purchasing party and the supplier 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 amount determination device is suitable for the case that the purchaser or supplier determines the minimum order amount of the material, and can be implemented by hardware and/or software, and is generally integrated in an intelligent device. As shown in fig. 4, the apparatus includes: a data acquisition module 401, a scenario determination module 402, a purchase index determination module 403, and a purchase amount determination module 404.

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

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

a purchase index determining module 403, configured to determine, for each demand scenario, purchase indexes under various minimum order quantity MOQ strategies;

and a purchase amount determining module 404, configured to determine a target purchase amount based on the purchase indicators in all demand scenarios.

In this embodiment, the device first acquires material demand data within a preset time period, then determines demand scenarios based on the material demand data, then determines purchase indexes under various minimum order quantity MOQ strategies for each demand scenario, and finally determines target purchase quantities based on the purchase indexes under all the demand scenarios. Therefore, the purchase quantity can be determined according to the material demand data in a certain time and the MOQ strategies under various scenes, the ordering mode that one customized product order is used for ordering the next material purchase order in the customized product is avoided, the time and labor cost of the purchaser are reduced, the production cost and the transportation cost of the supplier goose are reduced, and the matching satisfaction of the two parties is improved.

Further, the scene determining module 402 includes:

Further, the purchasing 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 strategies; and determining the purchasing times required by the newly increased demand based on the total purchasing times and the total newly increased demand times.

Further, the purchasing amount determining module 404 is specifically configured to determine, as the target purchasing amount, the purchasing amount of which the number of times of purchasing required by the new demand is greater than the preset purchasing number of times.

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

Further, the purchasing amount determining module 404 is specifically configured to determine, as the target purchasing amount, a purchasing amount in which a ratio of the total purchasing times to the number of purchasing times required by the new demand is greater than a preset value.

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

Example four

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

The memory 502 is a computer-readable storage medium, and can be used for storing software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the purchasing amount determination method in the embodiment of the present invention (for example, the modules in the purchasing amount determination device shown in fig. 4 include the data acquisition module 401, the scenario determination module 402, the purchasing index determination module 403, and the purchasing amount determination module 404). The processor 501 executes various functional applications of the device and data processing by executing software programs, instructions, and modules stored in the memory 502, that is, implements the purchase amount determination method described above.

The memory 502 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of the device, and the like. Further, the 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 devices through 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 the 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 purchase indexes under various minimum order quantity MOQ strategies aiming at each demand scene;

The input device 503 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the apparatus. The output device 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, on which a computer program is stored, where the computer program, when executed by a processing apparatus, implements the method for determining a purchase amount according to the first embodiment or the second embodiment of the present invention, where the method includes:

acquiring material demand data in a preset time period;

determining a demand scenario based on the material demand data;

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

From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.

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

It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. 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, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for determining a purchase amount, comprising:

acquiring material demand data in a preset time period;

determining a demand scenario based on the material demand data;

2. The method of claim 1, wherein determining a plurality of demand scenarios based on the material demand data comprises:

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

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

3. The procurement quantity determination method of claim 2 characterized by, the material demand data comprises: material coding and required quantity;

4. The method of claim 3, wherein generating a demand scenario based on the data occurrence rules comprises:

5. The method of claim 1, wherein determining the procurement metrics under the MOQ policy for the minimum orders comprises:

6. The method of claim 5, wherein determining the target procurement quantity based on the procurement indicators under all demand scenarios comprises:

7. The method of claim 1, wherein determining the procurement metrics under the MOQ policy for the minimum orders comprises:

8. The method of claim 7, wherein determining a target procurement quantity based on the procurement indicators under all demand scenarios comprises:

and determining the purchase quantity with the inventory turnover days smaller than the preset days as a target purchase quantity.

9. A purchase amount determining apparatus, comprising:

10. An apparatus, comprising:

one or more processors;

a memory for storing one or more programs;

the one or more programs being executable by the one or more processors to cause the one or more processors to implement the procurement quantity determination method of any of claims 1-8.

11. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method of determining a procurement amount according to any of claims 1 to 8.