CN113935684A

CN113935684A - Generation method and device of purchase order, computer equipment and storage medium

Info

Publication number: CN113935684A
Application number: CN202111182910.2A
Authority: CN
Inventors: 李永攀; 陈金辉; 何敏; 余海洋; 李渔燕
Original assignee: Kingdee Software China Co Ltd
Current assignee: Kingdee Software China Co Ltd
Priority date: 2021-10-11
Filing date: 2021-10-11
Publication date: 2022-01-14
Anticipated expiration: 2041-10-11

Abstract

The application relates to a method and a device for generating a purchase order, computer equipment and a storage medium. The method comprises the following steps: determining a plurality of candidate suppliers according to the expected supplier attribute and the expected material attribute in the purchasing scheme; determining the target weight of each evaluation dimension, determining the target evaluation score of each candidate supplier according to the target weight and historical purchasing data, and screening to obtain the target supplier; determining a material quota corresponding to each target provider according to the material demand in the purchasing scheme and the supply limit of each target provider; and finally, generating a purchase order matched with the purchase scheme based on the target suppliers and the material quotas corresponding to the target suppliers respectively. By adopting the method, the purchase order can be objectively and fairly automatically generated, and the selection result of the supplier is prevented from being influenced by human subjective factors.

Description

Generation method and device of purchase order, computer equipment and storage medium

Technical Field

The present application relates to the technical field of supply chain management, and in particular, to a method and an apparatus for generating a purchase order, a computer device, and a storage medium.

Background

At present, when an enterprise purchases and selects a provider, generally, according to experience, in a purchasing and sourcing stage, modes of inquiring price, bidding price and the like are manually appointed to carry out price comparison and calibration so as to finally place an order with the provider or directly appoint the provider to sign a contract or place an order, and the selection process of the provider is mainly carried out manually, so that the enterprise purchasing is easily influenced by artificial subjective factors and has low efficiency.

Disclosure of Invention

In view of the above, it is necessary to provide a method, an apparatus, a computer device, and a storage medium for generating a purchase order, which can automatically determine a supplier and its quota, thereby automatically generating the purchase order.

A method of generating a purchase order, the method comprising:

according to the expected supplier attribute and the expected material attribute in the purchasing scheme, matching is carried out in a pre-stored supplier list and a pre-stored material list, and a plurality of candidate suppliers are determined;

determining target weights of all evaluation dimensions, and determining target evaluation scores of each candidate supplier corresponding to different evaluation dimensions respectively according to the target weights of all evaluation dimensions and historical purchasing data;

determining at least one target supplier satisfying a screening condition among the plurality of candidate suppliers according to the target evaluation score;

according to the material demand in the purchasing scheme and the supply limit of each target provider, measuring whether each target provider can provide the material demand under the condition of the supply limit, and determining the material quota corresponding to each target provider according to the measurement result;

and generating a purchase order matched with the purchase scheme based on the target suppliers and the material quotas corresponding to the target suppliers respectively.

In one embodiment, the determining the target weight for each evaluation dimension includes:

establishing a dimension comparison matrix according to a plurality of evaluation dimensions and preset index importance levels;

calculating a feature vector of the dimension comparison matrix, and determining candidate weights corresponding to each evaluation dimension based on the feature vector;

carrying out consistency check on the dimension comparison matrix;

if the consistency check is passed, taking the candidate weight as the target weight of each evaluation dimension;

and if the consistency check is not passed, adjusting the dimension comparison matrix, returning to the step of establishing the dimension comparison matrix, and executing again until the consistency check is passed to obtain the target weight of each evaluation dimension.

In one embodiment, the determining the target assessment score of each candidate supplier corresponding to different assessment dimensions according to the target weight of each assessment dimension and the historical procurement data comprises:

respectively calculating a plurality of initial evaluation scores of each candidate supplier, which respectively correspond to different evaluation dimensions, according to historical purchasing data;

normalizing the initial evaluation scores under each evaluation dimension to obtain candidate evaluation scores corresponding to each evaluation dimension under the same evaluation standard;

determining the association degree of each candidate supplier corresponding to each evaluation dimension based on the candidate evaluation scores corresponding to each evaluation dimension;

and determining target evaluation scores of each candidate supplier corresponding to different evaluation dimensions respectively based on the relevance and the target weights of the evaluation dimensions.

In one embodiment, the determining the association degree of each candidate supplier corresponding to each evaluation dimension based on the candidate evaluation score corresponding to each evaluation dimension includes:

determining the absolute difference value of each candidate evaluation score and an evaluation standard based on the candidate evaluation scores corresponding to each evaluation dimension to obtain an absolute difference matrix;

for each candidate supplier, determining the most value in the candidate evaluation scores of the candidate suppliers under different evaluation dimensions based on the absolute difference matrix, and calculating the association degree of each candidate supplier corresponding to each evaluation dimension based on the most value.

In one embodiment, the procurement plan includes at least material demand; the supply limit at least comprises one of a material quota ratio, a maximum supply quantity, a minimum order quantity and a minimum packaging quantity; the measuring whether each target provider can provide the material demand amount under the condition of the supply limit according to the material demand amount in the purchasing scheme and the supply limit of each target provider, and determining the material quota corresponding to each target provider according to the measurement result, includes:

acquiring the type of the material to be quota at the current time;

determining a target supplier to be allocated corresponding to the material type of the current to-be-allocated amount based on the material allocation ratio and the total material allocation of each target supplier;

determining a material quota of the target provider to be quota corresponding to the material category of the current to-be-quota based on the material demand and at least one supply limit of a maximum supply quantity, a minimum order quantity and a minimum packaging quantity of the target provider to be quota;

updating the total material quota of the target supplier to be quota based on the material quota corresponding to the material type of the current to be quota;

and taking the next material type as the next material type to be quota, returning a ratio result according to the total order amount of each target supplier and the corresponding material quota ratio, and continuously executing the step of taking the target supplier corresponding to the minimum value as the target supplier to be quota corresponding to the material type to be quota until all the material types complete quota.

In one embodiment, the determining, based on the material quota ratio of each target provider and the total material quota, a target provider to be granted for the material category corresponding to the current to be granted includes:

for the material type of the current to-be-quota, if at least two target suppliers are not allocated with material quotas, taking the target supplier corresponding to the maximum value of the material quota ratio as the target supplier to be quota corresponding to the material type of the to-be-quota;

otherwise, calculating a ratio result of the total material quota of each target provider and the corresponding material quota ratio, and taking the target provider corresponding to the minimum value in the ratio result as the target provider to be quota corresponding to the material type to be quota.

In one embodiment, the determining, based on the material demand and at least one of a maximum supply amount, a minimum order amount, and a minimum package amount of the target provider to be allocated, a material allocation amount of the target provider to be allocated corresponding to a material category of the current amount to be allocated includes:

for the target provider to be quota, if the material demand is greater than the maximum supply quantity of the target provider to be quota, determining the material quota of the target provider to be quota corresponding to the current material category to be quota based on the maximum supply quantity and the minimum package quantity;

if the material demand is less than the minimum ordering quantity of the target supplier to be allocated, determining a material allocation of the target supplier to be allocated corresponding to the material type of the current amount to be allocated based on the minimum ordering quantity and the minimum packaging quantity;

and if the material demand is larger than the minimum ordering quantity of the target provider to be allocated and smaller than the maximum supply quantity of the target provider to be allocated, determining the material allocation of the target provider to be allocated corresponding to the material type of the current amount to be allocated based on the material demand and the minimum packaging quantity.

An apparatus for generating a purchase order, the apparatus comprising:

the matching module is used for matching in a pre-stored supplier list and a pre-stored material list according to the expected supplier attribute and the expected material attribute in the purchasing scheme to determine a plurality of candidate suppliers;

the evaluation module is used for determining the target weight of each evaluation dimension and determining the target evaluation score of each candidate supplier corresponding to different evaluation dimensions according to the target weight of each evaluation dimension and historical purchasing data;

a screening module for determining at least one target supplier satisfying a screening condition among the plurality of candidate suppliers according to the target evaluation score;

the quota module is used for measuring whether each target provider can provide the material demand under the condition of the supply limit according to the material demand in the purchase scheme and the supply limit of each target provider, and determining the material quota corresponding to each target provider according to the measurement result;

and the generating module is used for generating a purchasing order matched with the purchasing scheme based on each target provider and the material quota corresponding to each target provider.

A computer device comprising a memory storing a computer program and a processor implementing the steps of the method described above when executing the computer program.

A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method.

According to the method, the device, the computer equipment and the storage medium for generating the purchase order, a plurality of candidate suppliers are determined according to a purchase scheme, target suppliers are selected according to target weights of all evaluation dimensions and historical purchase data, material quotas corresponding to the target suppliers are determined according to the purchase scheme and supply limits of the target suppliers, and finally the target suppliers and the material quotas thereof automatically generate the purchase order matched with the purchase scheme. According to the method and the device, the suppliers can be automatically determined and the material quota is automatically distributed to each supplier, manual selection is not needed by experience, the selection result of the supplier is prevented from being influenced by artificial subjective factors, the generated purchase order more accurately meets the actual purchase requirement, the supplier is automatically selected to execute, and the efficiency is high.

Drawings

FIG. 1 is a flow diagram illustrating a method for generating a purchase order according to one embodiment;

FIG. 2 is a diagram illustrating the structure of the target and evaluation dimensions of the hierarchical analysis in one embodiment;

FIG. 3 is a diagram illustrating an overall generation of a purchase order according to one embodiment;

FIG. 4 is a diagram illustrating an overall generation method of a purchase order according to another embodiment;

FIG. 5 is a diagram illustrating an overall generation method of a purchase order according to still another embodiment;

FIG. 6 is a flowchart illustrating the steps of the terminal determining the target weights for each evaluation dimension in one embodiment;

FIG. 7 is a flowchart illustrating steps performed by the terminal to determine target assessment scores for each candidate provider for different assessment dimensions, according to one embodiment;

FIG. 8 is a flowchart illustrating steps performed by the terminal to determine relevancy of each candidate provider for each evaluation dimension in one embodiment;

fig. 9 is a flowchart illustrating steps of the terminal determining a material quota corresponding to each target provider in one embodiment;

FIG. 10 is a block diagram of an apparatus for generating a purchase order according to one embodiment;

FIG. 11 is a diagram illustrating an internal structure of a computer device in one embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

At present, performance management of a provider is disjointed with purchasing service, more than the method is that a provider range is manually appointed to inquire price, bid price and the like in a purchasing and source searching stage according to experience, and finally orders are placed with the provider through manual price comparison and calibration, or the provider is directly appointed to sign a contract or place orders, and recommendation is not carried out in combination with performance of the provider. Meanwhile, the allocation of the supplier quota is determined according to the fixed proportion, the fixed suppliers, the fixed priority order of the suppliers, manual assignment and the like according to experience, and is not objective enough; the supplier performance management evaluation dimension weight is manually specified, is not combined with historical business data, and is easily influenced by artificial subjective factors.

In view of the above, the present application provides a method, an apparatus, a computer device, and a storage medium for generating a purchase order, which define the evaluation dimensions of a supplier according to a purchase scheme, objectively calculate the proportion of each evaluation dimension according to an analytic hierarchy process, calculate a score for the supplier by using a gray correlation algorithm based on historical purchase data, automatically recommend the qualified supplier according to material and material classification in a purchase execution process, and reasonably allocate the qualified supplier to the supplier through a dynamic quota allocation scheme, wherein the whole process is objective, fair, transparent, efficient, and flexible.

In one embodiment, as shown in fig. 1, a method for generating a purchase order is provided, and this embodiment is illustrated by applying the method to a terminal, and it is to be understood that the method may also be applied to a server, and may also be applied to a system including a terminal and a server, and is implemented by interaction between the terminal and the server.

In this embodiment, the method includes the steps of:

and step S102, matching in a pre-stored supplier list and a pre-stored material list according to the expected supplier attribute and the expected material attribute in the purchasing scheme, and determining a plurality of candidate suppliers.

The purchasing scheme is used for indicating the target of the current purchasing so that the terminal can generate a purchasing order according to the target. Wherein, the procurement plan includes, but is not limited to, one or more of expected supplier attributes, expected material attributes, and material demand. The expected supplier attribute refers to a supplier attribute of a target of the purchase, and the supplier attribute includes, but is not limited to, one or more attributes of a category, a property, a size, a region of the supplier, and the like. The expected material attributes refer to the target material that needs to be purchased, and include, but are not limited to, one or more of classification, properties, and number of the material.

Specifically, the terminal may store a supplier list and a material list in a storage space in advance, determine an expected supplier attribute and an expected material attribute in the purchasing scheme according to the target of the purchasing, and perform query matching in the list according to the expected supplier attribute and the expected material attribute, thereby picking out a plurality of candidate suppliers for subsequent further decision making. The storage space may be a local memory space of the terminal, a storage medium of the cache space, or a cache area (Buffer) on the storage medium. The storage medium may include, among other things, read-only memory, random access memory, EEPROM (electrically erasable and programmable read-only memory), CD-ROM (compact disk read-only memory) or other optical disk storage, magnetic disk storage or other magnetic storage devices, flash memory, a usb disk, a removable hard disk, or any other medium that can be used to store the desired program code in the form of instructions or data structures and that can be accessed.

And step S104, determining the target weight of each evaluation dimension, and determining the target evaluation score of each candidate supplier corresponding to different evaluation dimensions respectively according to the target weight of each evaluation dimension and the historical purchasing data. Wherein the evaluation dimension is a factor/criterion to be considered when determining the final supplier, and the evaluation dimension includes, but is not limited to, one or more of cost, quality, price, return rate, and arrival time.

Specifically, the terminal first selects the evaluation dimensions considered in the evaluation of this time, and determines the target weights corresponding to the evaluation dimensions respectively. And then, the terminal calculates and determines target evaluation scores of each candidate supplier corresponding to different evaluation dimensions respectively according to the target weights of the evaluation dimensions and by combining historical purchasing data.

In some embodiments, the terminal utilizes analytic hierarchy processes to determine the weight of each evaluation dimension. The basic idea of the analytic hierarchy process is to stratify the problem to be analyzed; according to the nature of the problem and the general target to be achieved, the problem is decomposed into different composition factors, and the factors are aggregated and combined according to different levels according to the correlation influence and the subordination relation of the factors to form a multi-level analysis structure model; and finally, comparing the quality of the problems and arranging the problems. As shown in fig. 2, the terminal determines a target Z of the required decision (i.e. the problem to be analyzed) and determines a plurality of evaluation dimensions a1, … …, Ai, … …, Aj (i.e. factors/criteria to be considered when analyzing the problem).

And step S106, determining at least one target supplier meeting the screening condition from the candidate suppliers according to the target evaluation scores. The screening condition is used for the terminal to screen the candidate suppliers so as to determine the final one or more target suppliers. For example, the screening condition is the top 5 suppliers ranked from high to low according to the target assessment score. The screening conditions can be set in advance in the purchasing scheme.

Specifically, after determining target evaluation scores of each candidate supplier corresponding to different evaluation dimensions respectively, the terminal selects at least one supplier from the candidate suppliers according to screening conditions, thereby determining a final target supplier.

In some embodiments, the terminal may also determine whether it is consistent with the actual situation after determining the target provider. The actual situation refers to the actual supply condition of the supplier. If the deviation is caused by the actual situation (for example, the determined target provider is unable to supply goods due to unexpected accident), the terminal can also push the result of the target provider to the corresponding operator, and the result is manually adjusted by the operator.

Step S108, according to the material demand in the purchase scheme and the supply limit of each target provider, measuring whether each target provider can provide the material demand under the condition of the supply limit, and determining the material quota corresponding to each target provider according to the measurement result. Wherein, the purchasing scheme at least also comprises one of the total order amount and the material demand amount. The supply limit is used to characterize the supply capability of the supplier, including but not limited to one or more of a material quota ratio, a maximum supply amount, a minimum order amount, a minimum packaging amount, and the like. The material quota ratio refers to a purchasing ratio determined for each target provider in advance.

Specifically, the terminal measures whether each target provider can provide the material demand amount under the condition of the supply limit according to the material demand amount specified in the purchase scheme and the supply limit of each target provider based on the target of the current purchase, and determines the material quota corresponding to each target provider according to the measurement result.

Step S110, generating a purchase order matching the purchase plan based on each target provider and the material quota corresponding to each target provider.

Specifically, after sequentially determining the target providers and the material quotas corresponding to the target providers, the terminal generates purchase orders matched with the purchase schemes according to the material quotas so as to facilitate the subsequent purchase execution process. Illustratively, the terminal generates a purchase order in a preset format, the purchase order records target suppliers, and each target supplier has a corresponding material quota in a related record.

Therefore, the terminal automatically determines the provider according to the weight of the evaluation dimension and the historical purchasing data, and automatically performs material quota for the determined provider according to the purchasing requirement and the actual supply capacity of the provider, so as to generate the purchasing order.

According to the method for generating the purchase order, a plurality of candidate suppliers are determined according to the purchase scheme, the target suppliers are selected from the candidate suppliers according to the target weight and the historical purchase data of each evaluation dimension, the material quota corresponding to each target supplier is determined according to the purchase scheme and the supply limit of the target suppliers, finally the target suppliers and the material quotas of the target suppliers automatically generate the purchase order matched with the purchase scheme, the suppliers can be automatically determined, the material quotas are automatically distributed to the suppliers, manual selection is not needed, the selection result of the suppliers is prevented from being influenced by artificial subjective factors, the generated purchase order more accurately accords with the actual demand of purchase, and the automatic execution of the selection of the suppliers is realized, so that the efficiency is high.

In a specific embodiment, when the method for generating a purchase order provided by the user is applied to a scenario of automatically determining suppliers and their material quotas, an overall schematic diagram of the method may be as shown in fig. 3. The terminal firstly carries out purchasing scheme configuration, and after determining purchasing requirement/target, carries out evaluation dimension configuration. The terminal sequentially performs the steps of definition of evaluation dimensions, weight calculation and consistency check. The definition of the evaluation dimension refers to determining which evaluation dimension is taken as a consideration factor of the decision process. After the weight of each evaluation dimension is determined through consistency check, the terminal calls a hierarchical analysis algorithm and a gray relevance analysis algorithm in an algorithm library, calls historical purchasing data stored in a sample library, and comprehensively obtains the score (namely the target evaluation score) of each supplier, so that intelligent recommendation of the supplier is performed. And the terminal determines the material quota of each supplier based on the supply limit and the purchasing scheme of each supplier stored in the sample library. And finally, the terminal generates a purchase order according to the suppliers and the material quotas of the suppliers. The historical purchase data includes, for example, purchase management data (for example, data on orders, prices, and changes), inventory management data (for example, data on receiving, warehousing, and returning of goods), and management data due (for example, data on invoices, payments, and refunds). The generated purchase order may be used in subsequent inquiry, bidding, bid inviting, etc. scenarios.

In one embodiment, the method for generating the purchase order requested to be provided by the user can be represented by the flowchart shown in fig. 4. And the terminal sequentially performs purchase scheme configuration, evaluation dimension definition and dimension comparison matrix construction, and performs weight calculation according to the dimension comparison matrix. Then the terminal judges whether the terminal passes consistency check; if not, readjusting the matrix until the consistency test is passed; after passing the consistency check, the corresponding weight of each evaluation dimension can be determined. For the detailed process and steps, please refer to other embodiments, which are not described herein.

In one embodiment, the method for generating the purchase order requested to be provided by the user can be represented by the flowchart shown in fig. 5. The terminal sequentially performs purchasing scheme configuration, specifies required materials and material classification (namely expected material attributes) according to the purchasing scheme, and determines the score of the supplier by using an analytic hierarchy process and a grey correlation degree analytical process so as to determine the grade of the supplier score. At this time, if the terminal calculation result determines that there is no ranking (e.g., no provider satisfying the condition), the provider may be manually specified. After the terminal determines the ranking order of the suppliers, intelligent recommendation of the suppliers can be carried out according to the screening conditions, so that the suppliers can be selected. Then, the terminal allocates material quota for each selected supplier, and finally generates a purchase order. For the detailed process and steps, please refer to other embodiments, which are not described herein.

In some embodiments, as shown in fig. 6, the step of determining, by the terminal, the target weight of each evaluation dimension by using an analytic hierarchy process includes:

step S602, establishing a dimension comparison matrix according to a plurality of evaluation dimensions and preset index importance levels.

The index importance level is a scale for determining a dimension contrast matrix formed by each evaluation dimension, and is generally represented by a quantitative value indicating the importance degree of one evaluation dimension relative to the other evaluation dimension in comparison between the two evaluation dimensions. Illustratively, as shown in Table 1 below, the index importance level can be represented by a natural number of 1 ~ 9, where 1 represents that one of the two evaluation dimensions compared with each other is equally important with respect to the other evaluation dimension, and 9 represents that one of the two evaluation dimensions with each other is most important with respect to the other evaluation dimension, and vice versa, is represented by the reciprocal.

TABLE 1

Specifically, the terminal evaluates the data according to the set multiple valuesDimension and preset index importance level, comparing every two evaluation dimensions to obtain corresponding comparison results, namely quantization values, and constructing a dimension comparison matrix according to the obtained multiple quantization values. Illustratively, the terminal constructs a dimension contrast matrix A according to a plurality of evaluation dimensions A1, … …, Ai, … … and Aj and according to quantized value results of comparing each two evaluation dimensions i and j with each other_ij. Dimension contrast matrix A_ijCan be represented by the following formula:

for example, as shown in table 2 below, taking target Z as an example of cost optimization, for a plurality of evaluation dimensions a 1-a 5, the terminal compares two by two, and the obtained quantitative values of the index importance levels of each two evaluation dimensions are:

Z	A1	A2	A3	A4	A5
						A1	1	1/2	4	3	3
A2	2	1	7	5	5
						A3	1/4	1/7	1	1/2	1/3
A4	1/3	1/5	2	1	1
						A5	1/3	1/5	3	1	1

TABLE 2

Step S604, computing eigenvectors of the dimension contrast matrix, and determining candidate weights corresponding to the respective evaluation dimensions based on the eigenvectors.

Specifically, the terminal calculates a feature vector of the dimension comparison matrix according to the obtained dimension comparison matrix, and performs normalization processing based on the obtained feature vector to obtain candidate weights of each evaluation dimension.

Illustratively, the terminal SUMs up the columns of the dimension contrast matrix to obtain a SUM ═ Σ a_ij(ii) a Then the terminal carries out normalization processing on each column to obtain

And summing each column to obtain a feature vector W^T＝[∑A_ij]^T. The terminal carries out normalization processing on the feature vectors to obtain the weight of each evaluation dimension i

Step S606, consistency check is carried out on the dimension comparison matrix.

Wherein, the consistency check means using the consistency index and the consistency ratio<0.1 and a table of values for random consistency indices, for a dimension comparison matrix A_ijAnd (6) carrying out a checking process. The consistency ratio CR is generally defined as:

wherein, CI is a consistency index, and RI is a random consistency index. CI may be represented by the following formula:

where n denotes the number of evaluation dimensions, λ_max(A_ij) Is the largest feature root of the dimension contrast matrix. The RI can be obtained by a table lookup.

When the consistency ratio CR is less than 0.1, the dimension contrast matrix A is considered_ijIs within the allowable range, the terminal determines the dimension contrast matrix A_ijPass the consistency check. At this time, the terminal may use the candidate weight obtained after normalization as the target weight of each evaluation dimension.

When the consistency ratio CR is larger than or equal to 0.1, the terminal determines the dimension contrast momentArray A_ijThe consistency check cannot be passed, and the dimension contrast matrix A needs to be reconstructed at the moment_ijAnd comparing the matrix A to the dimension_ijMaking adjustments, i.e. to the dimension contrast matrix A_ijIs adjusted for each element value in the table.

Specifically, the terminal obtains the maximum characteristic root of the dimension comparison matrix through calculation, and calculates a consistency index according to the obtained maximum characteristic root, so that consistency check is performed on the dimension comparison matrix to determine that the relative importance of each evaluation dimension meets the consistency.

In step S608, if the consistency check passes, the candidate weight is used as the target weight of each evaluation dimension.

Specifically, when the consistency index of the dimension comparison matrix calculated by the terminal meets the consistency condition that the consistency ratio CR is less than 0.1, the consistency check of the dimension comparison matrix is determined to be passed, and the candidate weight is used as the target weight of each evaluation dimension.

And step S610, if the consistency check is not passed, adjusting the dimension comparison matrix, returning to the step of establishing the dimension comparison matrix, and executing again until the consistency check is passed, so as to obtain the target weight of each evaluation dimension.

Specifically, when the consistency index of the dimension comparison matrix calculated by the terminal does not meet the consistency condition that the consistency ratio CR is less than 0.1, determining that the consistency check of the dimension comparison matrix fails, and adjusting the values of all elements in the dimension comparison matrix to reconstruct the dimension comparison matrix until the consistency check of the dimension comparison matrix passes, so that the importance degree of each evaluation dimension is reasonably distributed. Therefore, the terminal obtains the final weight of each evaluation dimension.

In the embodiment, the proportion of each evaluation dimension is objectively calculated according to the analytic hierarchy process, the importance degree of each evaluation dimension can be objectively and fairly determined, the importance degree of each evaluation dimension is reasonably distributed, and the condition that the supplier selection is inaccurate due to artificial subjective factors is avoided.

In some embodiments, as shown in fig. 7, the step of determining, by the terminal, a target assessment score for each candidate supplier corresponding to a different assessment dimension according to the target weight and the historical procurement data for each assessment dimension includes:

step S702, respectively calculating a plurality of initial evaluation scores of each candidate supplier corresponding to different evaluation dimensions according to historical purchasing data.

Wherein the historical procurement data is derived from historical valid procurement orders, invoices, and payroll business data, etc., including but not limited to one or more of supply price, cost, quality, and delivery punctuality of the respective suppliers. According to the historical purchasing data, the historical purchasing condition of each candidate supplier can be determined and can be used as the reference data of the current purchasing order.

Specifically, the terminal respectively calculates a plurality of initial assessment scores of each candidate supplier corresponding to different assessment dimensions according to historical purchasing data. Illustratively, for example, if the assessment dimension A1 is a price, and the price of supplier 1 and supplier 2 in the historical procurement data are 100 dollars and 200 dollars, respectively, the terminal may calculate the initial assessment score of supplier 1 and supplier 2 in assessment dimension A1 and assessment dimension A1, respectively, as 100 and 200. For example, as shown in the following table 3, the terminal determines that the initial assessment scores of the suppliers 1 to 4 under the assessment dimensions a1 to a5 are respectively as follows:

assessing dimensionality	Supplier 1	Supplier 2	Supplier 3	Supplier 4
					A1	0	0.2	0	0.1
A2	2	1	3	5
					A3	150	200	170	145
A4	139	180	175	150
					A5	0	0.2	0.5	0.1

TABLE 3

Thus, the terminal first determines an initial assessment score for each candidate supplier, in each assessment dimension.

Step S704, perform normalization processing on the initial evaluation scores of the evaluation dimensions to obtain candidate evaluation scores corresponding to the evaluation dimensions under the same evaluation criterion.

Where direct comparison is not possible, since there are usually different dimensions and orders of magnitude between the various evaluation dimensions. In order to ensure the reliability and accuracy of the result, the initial evaluation score needs to be subjected to non-dimensionalization processing. After the non-dimensionalization processing is performed, each evaluation dimension is compared under the same evaluation standard, and the corresponding evaluation score can also be subjected to operations such as mathematical operation and the like under the same evaluation standard.

Specifically, the terminal performs normalization processing on the initial evaluation scores of the evaluation dimensions to obtain candidate evaluation scores corresponding to the evaluation dimensions under the same evaluation standard. Illustratively, taking the above table 3 as an example, the terminal may query the maximum value Max and the minimum value Min of each column, and perform normalization processing on each candidate evaluation score through the following formula, so as to convert the candidate evaluation scores of different dimensions into dimensionless values:

thus, as shown in table 4 below, the terminal normalizes the initial evaluation scores of the suppliers 1 to 4 in the evaluation dimensions a1 to a5, and obtains candidate evaluation scores under the same evaluation criterion (with 1 as the optimal value) as:

assessing dimensionality	Supplier 1	Supplier 2	Supplier 3	Supplier 4	Optimum value
						A1	0.1	0.2	0.1	0.43	1
A2	0.33	0.46	0.6	0.75	1
						A3	0.6	0.75	0.5	0.52	1
A4	0.4	0.25	0.5	0.67	1
						A5	0.57	0.2	0.25	0.2	1

TABLE 4

Therefore, the terminal obtains the candidate evaluation scores respectively corresponding to the suppliers under the same evaluation standard, each evaluation dimension, and the like, so that subsequent operations such as mathematical operation and the like are facilitated.

Step S706, determining the association degree of each candidate supplier corresponding to each evaluation dimension based on the candidate evaluation score corresponding to each evaluation dimension.

Specifically, the terminal calculates a correlation coefficient between the k-th evaluation dimension and the k-th optimal value of the ith supplier according to the obtained candidate evaluation scores of the candidate suppliers corresponding to the evaluation dimensions, so as to determine the correlation degree of the candidate suppliers corresponding to the evaluation dimensions.

In some embodiments, as shown in fig. 8, the step of determining, by the terminal, the association degree of each candidate supplier corresponding to each evaluation dimension based on the candidate evaluation score corresponding to each evaluation dimension includes:

step S802, determining the absolute difference value between each candidate evaluation score and the evaluation standard based on the candidate evaluation score corresponding to each evaluation dimension, and obtaining an absolute difference matrix.

Step S804, for each candidate supplier, determining the most value of the candidate evaluation scores of the candidate suppliers in different evaluation dimensions based on the absolute difference matrix, and calculating the association degree of each candidate supplier corresponding to each evaluation dimension based on the most value.

Under the same evaluation standard, each evaluation dimension corresponds to the same optimal value, and the closer each candidate evaluation score is to the optimal value, the better the evaluation score is. For example, with 1 as the evaluation criterion, the closer to 1 the respective candidate evaluation scores are, the better. Specifically, the terminal calculates absolute differences between the candidate evaluation scores and the evaluation standard to obtain an absolute difference matrix; determining the maximum value and the minimum value in the candidate evaluation scores of the candidate suppliers under different evaluation dimensions in the absolute difference matrix; calculating the association degree of each candidate supplier corresponding to each evaluation dimension according to the maximum value and the minimum value; each relevance constitutes a relevance matrix.

Illustratively, the terminal calculates the difference between the candidate evaluation score X of each candidate supplier in different evaluation dimensions and the evaluation criterion 1: 1-X and form an absolute difference matrix. Then, the terminal determines the maximum value Max and the minimum value Max of each column in the absolute difference matrix, and calculates the correlation coefficient according to the following formula:

where ∈ (i) is the degree of association, Max is the maximum value of each column in the dimensional contrast matrix, Min is the minimum value of each column in the dimensional contrast matrix, and σ is the resolution coefficient, where σ ∈ [0,1], and is usually taken as σ ═ 0.5. If the association degree of the ith candidate supplier is maximum, the ith candidate supplier is superior to other candidate suppliers.

In the embodiment, the candidate evaluation scores are calculated and processed according to the same evaluation standard, the gray characteristics among the evaluation dimensions are fully considered, the suppliers are objectively and accurately ranked for decision making, and the decision making efficiency is high.

Step S708, determining target assessment scores of each candidate supplier corresponding to different assessment dimensions respectively based on the association degrees and the target weights of the assessment dimensions.

Specifically, the terminal calculates and obtains target evaluation scores of each candidate supplier corresponding to different evaluation dimensions according to the weight of each evaluation dimension determined before and the calculated association degree and the product of the association degree and the weight.

For example, as shown in the following table 5, the terminal determines the correlation matrix and the weight W_iThe resulting matrix of the product, sums 100 over each column, thereby calculating a target valuation score for each candidate supplier as:

TABLE 5

Therefore, the terminal obtains the target evaluation scores of the candidate suppliers corresponding to different evaluation dimensions respectively, and the good and bad orders can be eliminated according to the target evaluation scores so as to determine the target suppliers.

In the embodiment, the grey correlation degree analysis method is used for analyzing and determining the final scores of the candidate suppliers, so that not only are quantitative and qualitative indexes scientifically processed, but also objective information and implicit grey characteristics of each evaluation dimension are fully utilized, the suppliers can be objectively and accurately sorted for decision making, and the decision making efficiency is high.

After the target suppliers are determined, the material quota of each target supplier needs to be determined according to the purchasing demand. In some embodiments, the terminal performs ranking according to target assessment scores of the candidate providers respectively corresponding to different assessment dimensions, and obtains the target providers according to preset screening conditions. And the terminal determines the material quota of each target provider one by one in sequence according to the sequencing of each target provider. For example, for a target provider with the highest target evaluation score, the terminal determines whether the material demand can be provided under the condition of the supply limit according to the maximum supply quantity, and if so, all the material demand is distributed to the target provider; if not, the target provider is assigned to the target provider according to its maximum supply. In other embodiments, as shown in fig. 9, the step of measuring, by the terminal, whether each target provider can provide the material demand under the condition of the supply limit according to the material demand in the purchase solution and the supply limit of each target provider, and determining, according to the measurement result, the material quota corresponding to each target provider includes:

step S902, obtaining the material type of the current to-be-quota.

Specifically, for multiple categories of materials, the terminal allocates quotas of different target providers to the materials of the various categories in sequence. The terminal can obtain the material type of the current to-be-quota according to the material sequence in the purchasing scheme or in a random selection mode, and determine the corresponding material demand.

Step S904, determining a target provider to be quota corresponding to the material category of the current to-be-quota based on the material quota ratio of each target provider and the total material quota.

Specifically, the terminal determines the target provider to be quota-allocated for the current material type to be quota based on the material quota proportion and the total material quota of each target provider. For the sake of distinction, this target provider is referred to as the current target provider to be granted.

In some embodiments, the step of determining, by the terminal, the target provider to be allocated corresponding to the material category of the current to-be-allocated amount based on the material allocation ratio of each target provider and the total material allocation includes: for the material type of the current to-be-quota, if the material quotas are not distributed to at least two target suppliers, taking the target supplier corresponding to the maximum value of the material quota ratio as the target supplier to be-quota corresponding to the material type of the to-be-quota; otherwise, calculating a ratio result of the total material quota of each target provider and the corresponding material quota ratio, and taking the target provider corresponding to the minimum value in the ratio result as the target provider to be quota corresponding to the material type to be quota.

Specifically, when the material quota is not started, since each target provider does not start the quota, the total material quota of each target provider is 0. Therefore, for the next material type to be quota, if at least two target suppliers have not been allocated material quotas, that is, the number of target suppliers whose ratio of the total material quota to the material quota ratio is 0 is greater than 1, determining the target supplier corresponding to the maximum value of the material quota ratio, and using the target supplier as the target supplier to be quota corresponding to the material type to be quota. Otherwise, if the number of the target suppliers with the ratio of the total material quota to the material quota ratio being 0 is not more than 1, calculating the ratio result of the total material quota of each target supplier to the corresponding material quota ratio, and taking the target supplier corresponding to the minimum value in the ratio result as the target supplier to be quota corresponding to the material type to be quota.

For example, suppose x represents the number of suppliers for one goods offering 1, … …, i, … …, x, the target suppliers are V1, V2, … …, Vx, respectively, and the ratio of each supplier is R1, R2, … …, Rx. The total order amount of each supplier is TQ1, TQ2, … … and TQx, the maximum supply amount of each supplier is Q1, Q2, … … and Qx, the minimum order amount of each supplier is Q1, Q2, … … and Qx, and the minimum package amount of each supplier is B1, B2, … … and Bx. Thus, the terminal determines the TQ_i/R_iIf the number of 0 is larger than 1, Max (R) is selected if this is true_i) V of_iIf not, calculating TQ as the provider of the current to-be-quota_i/R_iAnd select Min (TQ)_i/R_i) Corresponding V_iAs the provider of the current pending quota.

Step S906, determining a material quota corresponding to the current material category to be quota for the target provider to be quota based on the material demand amount and at least one of the maximum supply amount, the minimum order amount, and the minimum package amount of the target provider to be quota.

Specifically, in consideration of the supply limit of each target provider, the terminal calculates and obtains the material quota of the target provider to be quota corresponding to the material category of the current target provider to be quota according to the material demand of the material category of the current target provider to be quota and based on at least one supply limit of the maximum supply amount, the minimum order amount and the minimum package amount of the target provider to be quota, and allocates the material quota.

Step S908, updating the total material quota of the target provider to be quota based on the material quota of the material category corresponding to the current to-be-quota.

Specifically, after determining the material quota of the target provider to be allocated under the current material type to be allocated, the terminal uses the material quota as the total material quota of the target provider to be allocated, thereby completing the update of the total material quota of the target provider.

Step S910, taking the next material type as the next material type to be quota, and returning a ratio result according to the total order amount of each target provider and the corresponding material quota ratio, and continuing to execute the step of taking the target provider corresponding to the minimum value as the target provider to be quota corresponding to the material type to be quota until all the material types complete quota.

Specifically, after completing the material quota of a material type, the terminal selects a next material type according to the sequence in the purchase scheme or in a random selection mode, and takes the next material type as a next material type to be quota, and then processes a next material quota process. Namely, the process returns to step S904 to continue the execution. Therefore, the terminal respectively carries out material quota on all material types in the purchasing scheme in sequence until all the material types complete quota, and the material quota process is completed.

In some embodiments, the step of determining, by the terminal, a material quota corresponding to the current quota of the material category of the target provider to be quota based on the material demand amount and at least one of a maximum supply amount, a minimum order amount, and a minimum package amount of the target provider to be quota, includes:

step S1102, for the target provider to be quota, if the material demand is greater than the maximum supply quantity of the target provider to be quota, determining, based on the maximum supply quantity and the minimum package quantity, a material quota corresponding to the current material category to be quota for the target provider to be quota.

Specifically, the terminal first determines whether the material demand of the current material type to be allocated is greater than the maximum supply quantity of the target provider to be allocated. And if the material demand is greater than the maximum supply quantity of the target supplier to be quota, the quota target supplier cannot provide the material demand, and the terminal determines the material quota of the target supplier to be quota based on the maximum supply quantity and the minimum package quantity of the target supplier to be quota.

In some embodiments, if the material demand is greater than the maximum supply quantity of the target supplier to be quota, and the remainder of the maximum supply quantity and the minimum package quantity of the target supplier to be quota is zero, the terminal takes the maximum supply quantity as the material quota of the target supplier to be quota. On the contrary, if the remainder of the maximum supply quantity and the minimum package quantity of the target provider to be quota is not zero, the terminal performs rounding operation based on the maximum supply quantity and the minimum package quantity to obtain a rounding value, and the product of the rounding value and the minimum package quantity is used as the material quota of the target provider to be quota.

Specifically, when the terminal determines that the material demand is greater than the maximum supply quantity of the target supplier to be quota, the remainder of the maximum supply quantity and the minimum packaging quantity of the target supplier to be quota is calculated. And if the remainder is 0, the terminal takes the maximum supply quantity as the material quota of the target provider to be quota and distributes the material quota to the target provider to be quota. And if the remainder is not 0, the terminal performs rounding operation based on the maximum supply quantity and the minimum package quantity to obtain a rounding value, and the product of the rounding value and the minimum package quantity is used as the material quota of the target supplier to be quota and is distributed to the target supplier to be quota.

Also taking the assumption in the above embodiment as an example, if P>Q_iAnd is

The terminal will Q_iIs assigned to V_i(ii) a Wherein, B_i| A 0. If P>Q_iAnd is

The terminal will Int (Q)_i/B_i)*B_iIs assigned to V_i. Wherein,

is the remainder, Int (Q)_i/B_i) Is a rounded value.

Step S1104, if the material demand is less than the minimum order quantity of the target provider to be allocated, determining a material allocation amount of the target provider to be allocated corresponding to the current material type to be allocated based on the minimum order quantity and the minimum package quantity.

Specifically, if the terminal determines that the material demand is less than the maximum supply quantity of the target supplier to be quota, it indicates that the target supplier to be quota can provide the material demand. Thus, the terminal makes further decisions: whether the material demand is less than the minimum order quantity of the target supplier to be allocated. And if the material demand is less than the minimum ordering quantity of the target supplier to be allocated, which indicates that the minimum quantity of the quota is not less than the minimum ordering quantity of the target supplier to be allocated, the terminal determines the material quota of the target supplier to be allocated, which corresponds to the current material type to be allocated, based on the minimum ordering quantity and the minimum packaging quantity.

In some embodiments, if the material demand is less than the minimum order quantity of the target supplier to be batched, and the remainder of the minimum order quantity of the target supplier to be batched and the minimum packaging quantity is zero, the terminal takes the minimum order quantity as the material quota of the target supplier to be batched. On the contrary, if the remainder of the minimum order quantity and the minimum package quantity of the target supplier to be batched is not zero, the terminal performs rounding operation based on the minimum order quantity and the minimum package quantity to obtain a rounding value, and the sum of the product of the rounding value and the minimum package quantity is used as the material quota of the target supplier to be batched.

Specifically, when the terminal determines that the material demand is smaller than the minimum order quantity of the target supplier to be allocated, the remainder of the minimum order quantity and the minimum packaging quantity of the target supplier to be allocated is calculated. And if the remainder is 0, the terminal takes the minimum order quantity as a material quota of the target supplier to be quota, and allocates the quota. If the remainder is not 0, the terminal performs rounding operation based on the minimum order quantity and the minimum package quantity to obtain a rounding value, and the sum of the product of the rounding value and the minimum package quantity is used as the material quota of the target supplier to be quota.

Also taking the assumption in the above embodiment as an example, if P<q_iAnd is

The terminal will q_iIs assigned to V_i(ii) a If P<q_iAnd is

The terminal will Int (q)_i/B_i)*B_i+B_iIs assigned to V_i(ii) a Wherein,

is the remainder, Int (q)_i/B_i) Is a rounded value.

Step S1106, if the material demand is greater than the minimum order quantity of the target provider to be allocated and is less than the maximum supply quantity of the target provider to be allocated, determining a material allocation of the target provider to be allocated corresponding to the current material type to be allocated based on the material demand and the minimum package quantity.

Specifically, if the terminal determines that the material demand is greater than the minimum order quantity of the target supplier to be allocated and is less than the maximum supply quantity of the target supplier to be allocated, the terminal determines the material quota of the target supplier to be allocated based on the material demand and the minimum package quantity.

In some embodiments, if the material demand is greater than the minimum order quantity of the target supplier to be allocated and less than the maximum supply quantity of the target supplier to be allocated, the terminal calculates the remainder of the material demand and the minimum packaging quantity of the target supplier to be allocated. And if the remainder is 0, the terminal takes the material demand as a material quota of the target supplier to be quota, and allocates the quota. If the remainder is not 0, the terminal performs rounding operation on the material demand and the minimum package quantity to obtain a rounding value, then adds the minimum package quantity to the product of the rounding value and the minimum package quantity, and uses the final summation result as the material quota of the target supplier to be quota.

Also taking the assumption in the above embodiment as an example, if q is_i≤P≤Q_iAnd is

Then P is assigned to V_i(ii) a If q is_i≤P≤Q_iAnd is

Let Int (P/B)_i)*B_i+B_iIs assigned to V_i. Wherein,

is the remainder, Int (P/B)_i) Is a rounded value.

In the embodiment, whether each target provider can provide the material demand under the condition of the supply limit is measured according to the material demand in the purchase scheme and the supply limit of each target provider, and the material quota is allocated to each target provider according to the material demand, so that the purchase order can be objectively, fairly and efficiently generated; and the actual situation of the supplier is combined, and the purchase order is generated more accurately.

It should be understood that although the various steps in the flowcharts of fig. 1, 4-9 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 1, 4-9 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed alternately or at least partially with other steps or with at least some of the other steps.

In the embodiment, the weight and the supplier score are calculated by combining the analytic hierarchy process and the grey correlation degree analytical method and are used for intelligent recommendation of the supplier, but the analytic hierarchy process and the grey correlation degree analytical method are only one algorithm, deep learning can be performed by combining with the existing artificial intelligence algorithm, algorithm automatic recommendation can be performed by combining with the industry and purchasing classification of the client, and finally the purpose of automatically generating the purchasing order is achieved.

In one embodiment, as shown in fig. 10, there is provided a purchase order generation apparatus 1000, including: a matching module 1001, an evaluation module 1002, a screening module 1003, a quota module 1004, and a generation module 1005, wherein:

a matching module 1001, configured to perform matching in a pre-stored supplier list and material list according to the expected supplier attribute and the expected material attribute in the procurement plan, so as to determine multiple candidate suppliers.

The evaluation module 1002 is configured to determine a target weight of each evaluation dimension, and determine a target evaluation score corresponding to each candidate supplier in different evaluation dimensions according to the target weight of each evaluation dimension and historical procurement data.

A screening module 1003, configured to determine, according to the target evaluation score, at least one target provider that satisfies the screening condition among the candidate providers.

The quota module 1004 is configured to measure whether each target provider can provide the material demand under the condition of the supply limit according to the material demand in the purchase scheme and the supply limit of each target provider, and determine a material quota corresponding to each target provider according to a measurement result.

A generating module 1005, configured to generate a purchase order matched with the purchase scheme based on each target provider and the material quota corresponding to each target provider.

In one embodiment, the evaluation module is further configured to establish a dimension comparison matrix according to the plurality of evaluation dimensions and a preset index importance level; calculating a feature vector of the dimension comparison matrix, and determining candidate weights corresponding to each evaluation dimension based on the feature vector; carrying out consistency check on the dimension comparison matrix; if the consistency check is passed, taking the candidate weight as the target weight of each evaluation dimension; and if the consistency check is not passed, adjusting the dimension comparison matrix, returning to the step of establishing the dimension comparison matrix, and executing again until the consistency check is passed to obtain the target weight of each evaluation dimension.

In one embodiment, the evaluation module is further configured to calculate a plurality of initial evaluation scores corresponding to different evaluation dimensions of each candidate supplier respectively according to the historical procurement data; normalizing the initial evaluation scores under each evaluation dimension to obtain candidate evaluation scores corresponding to each evaluation dimension under the same evaluation standard; determining the association degree of each candidate supplier corresponding to each evaluation dimension based on the candidate evaluation scores corresponding to each evaluation dimension; and determining target evaluation scores of each candidate supplier corresponding to different evaluation dimensions respectively based on the association degrees and the target weights of the evaluation dimensions.

In one embodiment, the evaluation module is further configured to determine an absolute difference value between each candidate evaluation score and the evaluation criterion based on the candidate evaluation scores corresponding to each evaluation dimension, so as to obtain an absolute difference matrix; for each candidate supplier, determining the most value of candidate evaluation scores of the candidate suppliers under different evaluation dimensions based on the absolute difference matrix, and calculating the relevance of each candidate supplier corresponding to each evaluation dimension based on the most value.

In one embodiment, the procurement plan includes at least the material demand; the supply limit at least comprises one of a material quota ratio, a maximum supply quantity, a minimum order quantity and a minimum packaging quantity; the quota module is also used for acquiring the material type of the current to-be-quota; determining a target supplier to be subjected to quota corresponding to the material type of the current to-be-quota based on the material quota proportion and the total material quota of each target supplier; determining a material quota of the target provider to be quota corresponding to the material type of the current to-be-quota based on the material demand and at least one supply limit of the maximum supply quantity, the minimum ordering quantity and the minimum packaging quantity of the target provider to be quota; updating the total material quota of the target supplier to be quota based on the material quota corresponding to the material type of the current to be quota; and taking the next material type as the next material type to be quota, returning the ratio result of the total order amount of each target supplier and the corresponding material quota ratio, and continuously executing the step of taking the target supplier corresponding to the minimum value as the target supplier to be quota corresponding to the material type to be quota until all the material types complete quota.

In one embodiment, the quota module is further configured to, for a current material category to be quota, if at least two target providers have not been allocated material quotas, use a target provider corresponding to the maximum value of the material quota ratio as a target provider to be quota corresponding to the material category to be quota; otherwise, calculating a ratio result of the total material quota of each target provider and the corresponding material quota ratio, and taking the target provider corresponding to the minimum value in the ratio result as the target provider to be quota corresponding to the material type to be quota.

In one embodiment, the quota module is further configured to, for a target provider to be quota, determine, based on the maximum supply quantity and the minimum package quantity, a material quota corresponding to a current material category of the target provider to be quota, if the material demand quantity is greater than the maximum supply quantity of the target provider to be quota; if the material demand is smaller than the minimum ordering quantity of the target supplier to be allocated, determining a material allocation of the target supplier to be allocated corresponding to the current material type to be allocated based on the minimum ordering quantity and the minimum packaging quantity; and if the material demand is larger than the minimum ordering quantity of the target provider to be allocated and smaller than the maximum supply quantity of the target provider to be allocated, determining the material allocation of the target provider to be allocated corresponding to the current material type to be allocated based on the material demand and the minimum packaging quantity.

For the specific definition of the generation apparatus of the purchase order, reference may be made to the above definition of the generation method of the purchase order, and details are not described here. The modules in the purchase order generating device can be implemented in whole or in part by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, a computer device is provided, and the computer device may be the terminal in the foregoing embodiments, and its internal structure diagram may be as shown in fig. 11. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless communication can be realized through WIFI, an operator network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a method of generating a purchase order. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.

Those skilled in the art will appreciate that the architecture shown in fig. 11 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is further provided, which includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method embodiments when executing the computer program.

In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware related to instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above examples only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims

1. A method of generating a purchase order, the method comprising:

2. The method of claim 1, wherein determining the target weight for each evaluation dimension comprises:

carrying out consistency check on the dimension comparison matrix;

3. The method of claim 1, wherein determining a target valuation score for each candidate supplier for a different valuation dimension based on the target weight for each valuation dimension and historical procurement data comprises:

4. The method of claim 3, wherein determining the relevance of each candidate supplier for each evaluation dimension based on the candidate evaluation scores for each evaluation dimension comprises:

5. The method of claim 1, wherein the procurement plan includes at least a material demand; the supply limit at least comprises one of a material quota ratio, a maximum supply quantity, a minimum order quantity and a minimum packaging quantity; the measuring whether each target provider can provide the material demand amount under the condition of the supply limit according to the material demand amount in the purchasing scheme and the supply limit of each target provider, and determining the material quota corresponding to each target provider according to the measurement result, includes:

acquiring the type of the material to be quota at the current time;

6. The method of claim 5, wherein the determining the target provider of the to-be-allocated amount corresponding to the current to-be-allocated amount of the material category based on the material allocation ratios of the respective target providers and the total material allocation includes:

7. The method of claim 5, wherein the determining the material quota for the target provider to be quota corresponding to the material category of the current to be quota based on the material demand amount and at least one of a maximum supply amount, a minimum order amount, and a minimum package amount of the target provider to be quota comprises:

8. An apparatus for generating a purchase order, the apparatus comprising:

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.