CN117010922A - Cloud digital supply chain management system - Google Patents
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Abstract
The invention discloses a cloud digital supply chain management system and a cloud digital supply chain management method, and relates to the technical field of digital supply chains. The system comprises a user terminal and a cloud server, wherein the cloud server is used for determining a first difference coefficient and a second difference coefficient based on a first scoring index sequence and a second scoring index sequence uploaded by the user terminal, and determining a first weight corresponding to various first scoring indexes and a second weight corresponding to various second scoring indexes; determining a first weighted scoring sequence and a second weighted scoring sequence corresponding to each alternative provider, and obtaining a first target weighted scoring sequence and a second target weighted scoring sequence based on the first weighted scoring sequence; and determining the comprehensive score corresponding to each alternative provider based on the third difference coefficient and the fourth difference coefficient corresponding to each alternative provider so as to select the provider from a plurality of alternative providers. The system and the method disclosed by the invention can conveniently, quickly and accurately select the high-quality suppliers from the alternative suppliers.
Description
Technical Field
The invention belongs to the technical field of digital supply chains, and particularly relates to a cloud digital supply chain management system.
Background
In supply chain management, the selection of suppliers is an indispensable part, and a more common way in the prior art for selecting a quality supplier is to aggregate various data of a plurality of alternative suppliers, and then manually perform comparison analysis by related personnel according to the aggregated data, so as to select the quality supplier.
However, in this way, a large amount of manual analysis is required, which greatly increases labor and time costs and is prone to error. Therefore, how to provide an effective solution to conveniently, quickly and accurately select a good-quality supplier from alternative suppliers has become a urgent problem in the prior art.
Disclosure of Invention
The invention aims to provide a cloud digital supply chain management system and a cloud digital supply chain management method, which are used for solving the problems in the prior art.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
in a first aspect, the present invention provides a cloud digital supply chain management system comprising: the cloud terminal comprises a user terminal and a cloud server, wherein the user terminal is in communication connection with the cloud server;
the user terminal is used for uploading first scoring index sequences of a plurality of alternative suppliers and related to product quality and second scoring index sequences of the plurality of alternative suppliers and related to product cost to the cloud server, wherein the first scoring index sequences comprise at least one type of first scoring index, and the second scoring index sequences comprise at least one type of second scoring index;
The cloud server is used for determining a first difference coefficient of each type of first scoring index and a second difference coefficient of each type of second scoring index based on the first scoring index sequences corresponding to the plurality of alternative suppliers and the second scoring index sequences corresponding to the plurality of alternative suppliers;
the cloud server is further used for determining first weights corresponding to the first scoring indexes and second weights corresponding to the second scoring indexes based on the first difference coefficients of the first scoring indexes and the second difference coefficients of the second scoring indexes;
the cloud server is further configured to determine a first weighted score sequence corresponding to each alternative provider of the plurality of alternative providers and a second weighted score sequence corresponding to each alternative provider of the plurality of alternative providers based on a first weight corresponding to each type of first score index and a second weight corresponding to each type of second score index;
the cloud server is further configured to select a maximum value of a plurality of first weighted scores corresponding to each type of first score index from the first weighted score sequences corresponding to the plurality of alternative suppliers, obtain a first target weighted score sequence, and select a minimum value of a plurality of second weighted scores corresponding to each type of second score index from the second weighted score sequences corresponding to the plurality of alternative suppliers, obtain a second target weighted score sequence;
The cloud server is further configured to calculate a difference between a first weighted score sequence corresponding to each candidate provider and the first target weighted score sequence in the plurality of candidate providers, obtain a third difference coefficient corresponding to each candidate provider, and calculate a difference between a second weighted score sequence corresponding to each candidate provider and the second target weighted score sequence in the plurality of candidate providers, obtain a fourth difference coefficient corresponding to each candidate provider;
the cloud server is further configured to determine a composite score corresponding to each candidate provider based on the third difference coefficient corresponding to each candidate provider and the fourth difference coefficient corresponding to each candidate provider, so as to select a provider from the plurality of candidate providers based on the composite score corresponding to each candidate provider.
Based on the disclosure, the method and the system are used for uploading the first scoring index sequences of the multiple alternative suppliers and related to the product quality and the second scoring index sequences of the multiple alternative suppliers and related to the product cost to the cloud server through the user terminal; the cloud server is used for determining a first difference coefficient of each type of first scoring index and a second difference coefficient of each type of second scoring index based on a first scoring index sequence corresponding to a plurality of alternative suppliers and a second scoring index sequence corresponding to the plurality of alternative suppliers; determining a first weight corresponding to each type of first scoring index and a second weight corresponding to each type of second scoring index based on the first difference coefficient of each type of first scoring index and the second difference coefficient of each type of second scoring index; determining a first weighted scoring sequence corresponding to each alternative provider in the plurality of alternative providers and a second weighted scoring sequence corresponding to each alternative provider in the plurality of alternative providers based on the first weights corresponding to the various first scoring indexes and the second weights corresponding to the various second scoring indexes; then, selecting the maximum value of a plurality of first weighted scores corresponding to various first scoring indexes from the first weighted score sequences corresponding to the plurality of alternative suppliers to obtain a first target weighted score sequence, and selecting the minimum value of a plurality of second weighted scores corresponding to various second scoring indexes from the second weighted score sequences corresponding to the plurality of alternative suppliers to obtain a second target weighted score sequence; then calculating the difference between the first weighted score sequence corresponding to each alternative provider and the first target weighted score sequence in the plurality of alternative providers to obtain a third difference coefficient corresponding to each alternative provider, and calculating the difference between the second weighted score sequence corresponding to each alternative provider and the second target weighted score sequence in the plurality of alternative providers to obtain a fourth difference coefficient corresponding to each alternative provider; and finally, determining the comprehensive scores corresponding to the alternative suppliers based on the third difference coefficient corresponding to each alternative supplier and the fourth difference coefficient corresponding to each alternative supplier so as to select the supplier from a plurality of alternative suppliers based on the comprehensive scores corresponding to the alternative suppliers. In this way, the alternative suppliers can be comprehensively scored from the first scoring index related to the product quality and the second scoring index related to the product cost, so that the comprehensive score corresponding to the alternative supplier with high product quality and low product cost is higher, and the high-quality supplier can be determined from the two dimensions of the product quality and the product finished product.
Through the design, the invention can conveniently, quickly and accurately select high-quality suppliers from alternative suppliers according to the two dimensions of the product quality and the product finished product, avoids the problems that a great deal of labor cost and time cost are required to be consumed in manual analysis and the analysis is easy to make mistakes, and is convenient for practical application and popularization.
In one possible design, the cloud server is configured to determine a first difference coefficient of each type of first score index and a second difference coefficient of each type of second score index based on the first score index sequences corresponding to the plurality of alternative suppliers and the second score index sequences corresponding to the plurality of alternative suppliers, where the cloud server is specifically configured to:
establishing a first scoring index matrix and a second scoring index matrix corresponding to the multiple alternative suppliers according to a first scoring index sequence corresponding to the multiple alternative suppliers and a second scoring index sequence corresponding to the multiple alternative suppliers, wherein each row of the first scoring index matrix corresponds to the first scoring index sequence of one alternative supplier, each row of the second scoring index matrix corresponds to the second scoring index sequence of one alternative supplier, each column of the first scoring index matrix corresponds to multiple first scoring indexes which are in the same type and are in one-to-one correspondence with the multiple alternative suppliers, and each column of the second scoring index matrix corresponds to multiple second scoring indexes which are in the same type and are in one-to-one correspondence with the multiple alternative suppliers;
Calculating the information entropy of each type of first scoring index in the first scoring index matrix and the information entropy of each type of second scoring index in the second scoring index matrix;
and determining the difference degree of each type of first scoring index based on the information entropy of each type of first scoring index in the first scoring index matrix, and determining the difference degree of each type of second scoring index based on the information entropy of each type of second scoring index in the second scoring index matrix.
In one possible design, the cloud server is further configured to, before calculating the information entropy of each type of first scoring index in the first scoring index matrix and the information entropy of each type of second scoring index in the second scoring index matrix:
and normalizing the first scoring index matrix and the second scoring index matrix corresponding to the plurality of alternative suppliers.
In one possible design, the cloud server is specifically configured to, when determining the first weights corresponding to the first scoring indexes of the types and the second weights corresponding to the second scoring indexes of the types based on the first difference coefficient of the first scoring indexes of the types and the second difference coefficient of the second scoring indexes of the types:
Determining a first weight which corresponds to each type of first scoring index and is positively correlated with the difference degree based on the difference degree of each type of first scoring index;
and determining second weights which correspond to the second scoring indexes and are positively correlated with the difference degrees based on the difference degrees of the second scoring indexes.
In one possible design, when the cloud server is configured to calculate the degree of difference between the first weighted score sequence corresponding to each candidate provider and the first target weighted score sequence of the candidate providers, obtain a third degree of difference coefficient corresponding to each candidate provider, and calculate the degree of difference between the second weighted score sequence corresponding to each candidate provider and the second target weighted score sequence of the candidate providers, obtain a fourth degree of difference coefficient corresponding to each candidate provider, the cloud server is specifically configured to:
respectively converting a first weighted scoring sequence and a second weighted scoring sequence corresponding to each alternative provider in the plurality of alternative providers into vectors to obtain a first vector and a second vector corresponding to each alternative provider;
respectively converting the first target weighted scoring sequence and the second target weighted scoring sequence into vectors to obtain a third vector and a fourth vector;
Calculating Euclidean distance between the first vector corresponding to each alternative provider and the third vector to obtain a third difference coefficient corresponding to each alternative provider;
and calculating Euclidean distance between the second vector corresponding to each alternative provider and the fourth vector to obtain a fourth difference coefficient corresponding to each alternative provider.
In one possible design, the cloud server is specifically configured to, when determining the composite score corresponding to each candidate provider based on the third difference coefficient corresponding to each candidate provider and the fourth difference coefficient corresponding to each candidate provider:
and calculating the comprehensive score corresponding to each alternative provider through a TOPSIS algorithm based on the third difference coefficient corresponding to each alternative provider and the fourth difference coefficient corresponding to each alternative provider.
In one possible design, the first scoring index sequence includes a product quality index and/or an after-market service index, and the second scoring index sequence includes a price index and/or a logistics cost index.
In one possible design, the cloud server is further configured to rank the multiple candidate providers based on the composite scores corresponding to the candidate providers, and send the ranking result to the user terminal.
In one possible design, the cloud server is specifically configured to, when configured to send the ranking result to the user terminal:
and sending a plurality of alternative suppliers which are ranked ahead in the ranking result to the user terminal.
In a second aspect, the present invention provides a cloud digital supply chain management method, applied to a cloud server, the method comprising:
receiving a first scoring index sequence which is uploaded by a user terminal and is related to the product quality of a plurality of alternative suppliers and a second scoring index sequence which is uploaded by the user terminal and is related to the product cost of the plurality of alternative suppliers, wherein the first scoring index sequence comprises at least one type of first scoring index, and the second scoring index sequence comprises at least one type of second scoring index;
determining a first difference coefficient of each type of first scoring index and a second difference coefficient of each type of second scoring index based on the first scoring index sequences corresponding to the plurality of alternative suppliers and the second scoring index sequences corresponding to the plurality of alternative suppliers;
determining a first weight corresponding to each type of first scoring index and a second weight corresponding to each type of second scoring index based on the first difference coefficient of each type of first scoring index and the second difference coefficient of each type of second scoring index;
Determining a first weighted scoring sequence corresponding to each alternative provider of the plurality of alternative providers and a second weighted scoring sequence corresponding to each alternative provider of the plurality of alternative providers based on the first weights corresponding to the various first scoring indexes and the second weights corresponding to the various second scoring indexes;
selecting the maximum value of a plurality of first weighted scores corresponding to various first scoring indexes from the first weighted score sequences corresponding to the plurality of alternative suppliers to obtain a first target weighted score sequence, and selecting the minimum value of a plurality of second weighted scores corresponding to various second scoring indexes from the second weighted score sequences corresponding to the plurality of alternative suppliers to obtain a second target weighted score sequence;
calculating the difference between the first weighted score sequence corresponding to each alternative provider and the first target weighted score sequence in the plurality of alternative providers to obtain a third difference coefficient corresponding to each alternative provider, and calculating the difference between the second weighted score sequence corresponding to each alternative provider and the second target weighted score sequence in the plurality of alternative providers to obtain a fourth difference coefficient corresponding to each alternative provider;
And determining comprehensive scores corresponding to the alternative suppliers based on the third difference coefficient corresponding to the alternative suppliers and the fourth difference coefficient corresponding to the alternative suppliers, so as to select the supplier from the alternative suppliers based on the comprehensive scores corresponding to the alternative suppliers.
The beneficial effects are that:
the cloud digital supply chain management system and the cloud digital supply chain management method provided by the application can be used for conveniently, quickly and accurately selecting high-quality suppliers from alternative suppliers from the two dimensions of product quality and product finished products, avoid the problems that a great deal of labor cost and time cost are required to be consumed for manual analysis, and are easy to analyze errors, and are convenient for practical application and popularization.
Drawings
Fig. 1 is a schematic block diagram of a cloud digital supply chain management system according to an embodiment of the present application;
fig. 2 is a flowchart of a cloud digital supply chain management method according to an embodiment of the present application.
Detailed Description
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the present application will be briefly described below with reference to the accompanying drawings and the description of the embodiments or the prior art, and it is obvious that the following description of the structure of the drawings is only some embodiments of the present application, and other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art. It should be noted that the description of these examples is for aiding in understanding the present application, but is not intended to limit the present application.
It will be understood that, although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of example embodiments of the present invention.
It should be understood that for the term "and/or" that may appear herein, it is merely one association relationship that describes an associated object, meaning that there may be three relationships, e.g., a and/or B, may represent: a alone, B alone, and both a and B; for the term "/and" that may appear herein, which is descriptive of another associative object relationship, it means that there may be two relationships, e.g., a/and B, it may be expressed that: a alone, a alone and B alone; in addition, for the character "/" that may appear herein, it is generally indicated that the context associated object is an "or" relationship.
In order to conveniently, quickly and accurately select a high-quality supplier from alternative suppliers, embodiments in the community provide a cloud digital supply chain management system and a method, which can conveniently, quickly and accurately select a high-quality supplier from the alternative suppliers from two dimensions of product quality and product finished products.
Fig. 1 is a schematic block diagram of a cloud digital supply chain management system according to a first aspect of the present application, where the cloud digital supply chain management system includes a user terminal and a cloud server, and the user terminal is in communication connection with the cloud server.
The user terminal is configured to upload a first scoring index sequence of a plurality of alternative suppliers and related to product quality and a second scoring index sequence of the plurality of alternative suppliers and related to product cost to the cloud server, where the first scoring index sequence includes at least one type of first scoring index, and the second scoring index sequence includes at least one type of second scoring index. The cloud server is used for determining a first difference coefficient of each type of first scoring index and a second difference coefficient of each type of second scoring index based on the first scoring index sequences corresponding to the plurality of alternative suppliers and the second scoring index sequences corresponding to the plurality of alternative suppliers. The cloud server is further used for determining first weights corresponding to the first scoring indexes and second weights corresponding to the second scoring indexes based on the first difference coefficients of the first scoring indexes and the second difference coefficients of the second scoring indexes. The cloud server is further configured to determine a first weighted score sequence corresponding to each candidate provider of the plurality of candidate providers and a second weighted score sequence corresponding to each candidate provider of the plurality of candidate providers based on the first weights corresponding to the various first score indicators and the second weights corresponding to the various second score indicators. The cloud server is further configured to select a maximum value of a plurality of first weighted scores corresponding to each type of first score index from the first weighted score sequences corresponding to the plurality of candidate suppliers, obtain a first target weighted score sequence, and select a minimum value of a plurality of second weighted scores corresponding to each type of second score index from the second weighted score sequences corresponding to the plurality of candidate suppliers, obtain a second target weighted score sequence. The cloud server is further configured to calculate a difference between a first weighted score sequence corresponding to each candidate provider and the first target weighted score sequence in the plurality of candidate providers, obtain a third difference coefficient corresponding to each candidate provider, and calculate a difference between a second weighted score sequence corresponding to each candidate provider and the second target weighted score sequence in the plurality of candidate providers, obtain a fourth difference coefficient corresponding to each candidate provider. The cloud server is further configured to determine a composite score corresponding to each candidate provider based on the third difference coefficient corresponding to each candidate provider and the fourth difference coefficient corresponding to each candidate provider, so as to select a provider from the plurality of candidate providers based on the composite score corresponding to each candidate provider.
The user terminal is used for uploading a first scoring index sequence which is related to the product quality and provided with a plurality of alternative suppliers and a second scoring index sequence which is related to the product cost and provided with a plurality of alternative suppliers to the cloud server, wherein the first scoring index sequence comprises at least one type of first scoring index, and the second scoring index sequence comprises at least one type of second scoring index. In the embodiment of the application, the first scoring index sequence and the second scoring index sequence of the plurality of alternative suppliers can be obtained by statistical analysis according to the supplier information of the plurality of alternative suppliers and the historical acquisition records corresponding to the plurality of alternative suppliers. The first scoring index sequence is related to product quality, which may include, but is not limited to, product quality index and/or after-market service index, and the second scoring index sequence is related to product cost, which may include, but is not limited to, price index and/or logistics cost index.
The product quality index can be used for representing the quality of products, such as product percent of pass, product error, product specification grade and the like, and the better the product quality is, the higher the corresponding product quality index is. The after-sales service index is used for representing the quality of after-sales service, such as after-sales maintenance time, after-sales maintenance projects and the like, and the longer the after-sales service time is, the more the after-sales maintenance projects are, the higher the corresponding after-sales service index is. The price index is used for representing the price of the product, and the lower the price of the product is relative to the market average price, the lower the corresponding price index is. The logistic cost index is used for representing the logistic cost of the product, such as the logistic distance, and the lower the logistic cost is, the lower the corresponding logistic cost index is.
The cloud server is used for determining a first difference coefficient of each type of first scoring index and a second difference coefficient of each type of second scoring index based on a first scoring index sequence corresponding to a plurality of alternative suppliers and a second scoring index sequence corresponding to the plurality of alternative suppliers.
Specifically, the cloud server may first establish a first scoring index matrix and a second scoring index matrix corresponding to the multiple alternative suppliers according to the first scoring index sequences corresponding to the multiple alternative suppliers and the second scoring index sequences corresponding to the multiple alternative suppliers, where each row of the first scoring index matrix corresponds to the first scoring index sequence of one alternative supplier, each row of the second scoring index matrix corresponds to the second scoring index sequence of one alternative supplier, each column of the first scoring index matrix corresponds to multiple first scoring indexes of the same type and corresponding to the multiple alternative suppliers one by one, and each column of the second scoring index matrix corresponds to multiple second scoring indexes of the same type and corresponding to the multiple alternative suppliers one by one.
For example, if m candidate suppliers have n types of first scoring indexes in the first scoring index sequence and o types of first scoring indexes in the second scoring index sequence, the first scoring index sequence corresponding to the ith candidate supplier can be expressed as X i ＝(a i1 ，a i2 ，......,a in )，a in Representing the nth class of first scoring index in the first scoring index sequence corresponding to the ith alternative provider, wherein the second scoring index sequence corresponding to the ith alternative provider can be represented as Y i ＝(b i1 ，b i2 ，....b io )，b io And the first scoring index of the o-th class in the second scoring index sequence corresponding to the i-th alternative provider is represented, and i is more than or equal to 1 and less than or equal to m.
The first scoring index matrix corresponding to the plurality of alternative suppliers may be represented asThe second scoring index matrix corresponding to the plurality of alternative suppliers may be expressed as +.>
After the first scoring index matrix and the second scoring index matrix corresponding to the multiple alternative suppliers are established, information entropy of each type of first scoring index in the first scoring index matrix and information entropy of each type of second scoring index in the second scoring index matrix can be calculated. And then determining the difference degree of each type of first scoring index based on the information entropy of each type of first scoring index in the first scoring index matrix, and determining the difference degree of each type of second scoring index based on the information entropy of each type of second scoring index in the second scoring index matrix.
In one or more embodiments, before calculating the information entropy of each type of first scoring index in the first scoring index matrix and the information entropy of each type of second scoring index in the second scoring index matrix, the first scoring index matrix and the second scoring index matrix corresponding to the multiple alternative suppliers may be normalized, so as to facilitate calculation.
In the embodiment of the application, the information entropy of the j types of first scoring indexes in the first scoring index matrix can be expressed asWherein A is ij And (3) representing the j-th class of first scoring indexes (corresponding normalized values) in the first scoring index matrix corresponding to the i-th alternative supplier, and m represents the total number of the alternative suppliers. Similarly, the information entropy of each type of second scoring index in the second scoring index matrix can also be calculated by adopting the same calculation mode.
In the embodiment of the application, the cloud server determines the first weights corresponding to the various first scoring indexes and the second weights corresponding to the various second scoring indexes based on the first difference coefficient of the various first scoring indexes and the second difference coefficient of the various second scoring indexes. The first weights corresponding to the first scoring indexes and positively correlated with the difference degrees can be determined based on the difference degrees of the first scoring indexes, and the second weights corresponding to the second scoring indexes and positively correlated with the difference degrees can be determined based on the difference degrees of the second scoring indexes. I.e. the greater the degree of difference, the greater the corresponding weight.
The cloud server is further configured to determine a first weighted score sequence corresponding to each of the plurality of alternative suppliers and a second weighted score sequence corresponding to each of the plurality of alternative suppliers based on the first weights corresponding to the various first score indexes and the second weights corresponding to the various second score indexes.
Specifically, the first scoring index sequences corresponding to the alternative suppliers may multiply each first scoring index of the first scoring index sequences by the first weight corresponding to the first scoring index to obtain a first weighted scoring sequence corresponding to each alternative supplier. And multiplying each second scoring index of the second scoring index sequence by a second weight corresponding to the second scoring index sequence corresponding to each alternative provider to obtain a second weighted scoring sequence corresponding to each alternative provider.
The cloud server is further configured to select a maximum value of a plurality of first weighted scores corresponding to each type of first score index from the first weighted score sequences corresponding to the plurality of alternative suppliers, obtain a first target weighted score sequence, and select a minimum value of a plurality of second weighted scores corresponding to each type of second score index from the second weighted score sequences corresponding to the plurality of alternative suppliers, obtain a second target weighted score sequence.
For example, the number of candidate suppliers is 3, the first weighted score sequence includes 4 weighted scores, the first weighted score sequence corresponding to the 1 st candidate supplier is a11, a12, a13, a14, the first weighted score sequence corresponding to the 2 nd candidate supplier is a21, a22, a23, a24, and the first weighted score sequence corresponding to the 3 rd candidate supplier is a31, a32, a33, a34. Wherein a11, a21 and a31 are a plurality of first weighted scores corresponding to the class 1 first score index, a12, a22 and a32 are a plurality of first weighted scores corresponding to the class 2 first score index, a13, a23 and a33 are a plurality of first weighted scores corresponding to the class 3 first score index, and a14, a24 and a34 are a plurality of first weighted scores corresponding to the class 4 first score index. Then a maximum first weighted score AX1 (X is 1, 2 or 3) may be selected from a11, a21 and a31, a maximum first weighted score AY2 (Y is 1, 2 or 3) may be selected from a12, a22 and a32, a maximum first weighted score AZ3 (Z is 1, 2 or 3) may be selected from a13, a23 and a33, a maximum first weighted score AM4 (M is 1, 2 or 3) may be selected from a14, a24 and a34, and then the sequence of AX1, AY2, AZ3 and AM4 may be used as the first target weighted score sequence. Similarly, the second target weighted score sequence can be determined, and the specification needs to be that, in consideration of cost, when selecting the suppliers, the suppliers with lower cost should be selected as much as possible, so that the second target weighted score sequence is the minimum value in a plurality of second weighted scores corresponding to various second score indexes selected from the second weighted score sequences corresponding to a plurality of alternative suppliers.
The cloud server is further configured to calculate a difference between a first weighted score sequence corresponding to each candidate provider and a first target weighted score sequence of the candidate providers, obtain a third difference coefficient corresponding to each candidate provider, and calculate a difference between a second weighted score sequence corresponding to each candidate provider and a second target weighted score sequence of the candidate providers, obtain a fourth difference coefficient corresponding to each candidate provider.
Specifically, the cloud server may convert the first weighted score sequence and the second weighted score sequence corresponding to each candidate provider in the plurality of candidate providers into vectors, to obtain a first vector and a second vector corresponding to each candidate provider. And converting the first target weighted scoring sequence and the second target weighted scoring sequence into vectors to obtain a third vector and a fourth vector respectively. And then calculating the vector distance between the first vector and the third vector corresponding to each alternative provider to obtain a third difference coefficient corresponding to each alternative provider, and calculating the vector distance between the second vector and the fourth vector corresponding to each alternative provider to obtain a fourth difference coefficient corresponding to each alternative provider. The vector distance between the first vector and the third vector and the vector distance between the second vector and the fourth vector may be, but are not limited to, euclidean distance, cosine similarity, etc., which are not specifically limited in the embodiment of the present application.
The cloud server is further configured to determine a composite score corresponding to each candidate provider based on the third difference coefficient corresponding to each candidate provider and the fourth difference coefficient corresponding to each candidate provider, so as to select a provider from the plurality of candidate providers based on the composite score corresponding to each candidate provider.
In the embodiment of the present application, the comprehensive score corresponding to each candidate provider may be calculated by using a TOPSIS algorithm (Technique for Order Preference by Similarity to an Ideal Solution, which is often simply called a good-bad solution distance method in China) based on the third difference coefficient corresponding to each candidate provider and the fourth difference coefficient corresponding to each candidate provider, which is not described in detail in the embodiment of the present application.
In one or more embodiments, the cloud server is further configured to rank the multiple candidate providers based on the composite scores corresponding to the candidate providers, and send the ranking result to the user terminal. When the sorting result is sent to the user terminal, a plurality of alternative suppliers with top sorting in the sorting result can also be sent to the user terminal, so that relevant personnel of the user terminal can select one or more alternative suppliers with good product quality and low product cost from the sorting result as suppliers.
In summary, the cloud digital supply chain management system provided by the embodiment of the application is used for uploading the first scoring index sequences of the multiple alternative suppliers and related to the product quality and the second scoring index sequences of the multiple alternative suppliers and related to the product cost to the cloud server through the user terminal; the cloud server is used for determining a first difference coefficient of each type of first scoring index and a second difference coefficient of each type of second scoring index based on a first scoring index sequence corresponding to a plurality of alternative suppliers and a second scoring index sequence corresponding to the plurality of alternative suppliers; determining a first weight corresponding to each type of first scoring index and a second weight corresponding to each type of second scoring index based on the first difference coefficient of each type of first scoring index and the second difference coefficient of each type of second scoring index; determining a first weighted scoring sequence corresponding to each alternative provider in the plurality of alternative providers and a second weighted scoring sequence corresponding to each alternative provider in the plurality of alternative providers based on the first weights corresponding to the various first scoring indexes and the second weights corresponding to the various second scoring indexes; then, selecting the maximum value of a plurality of first weighted scores corresponding to various first scoring indexes from the first weighted score sequences corresponding to the plurality of alternative suppliers to obtain a first target weighted score sequence, and selecting the minimum value of a plurality of second weighted scores corresponding to various second scoring indexes from the second weighted score sequences corresponding to the plurality of alternative suppliers to obtain a second target weighted score sequence; then calculating the difference between the first weighted score sequence corresponding to each alternative provider and the first target weighted score sequence in the plurality of alternative providers to obtain a third difference coefficient corresponding to each alternative provider, and calculating the difference between the second weighted score sequence corresponding to each alternative provider and the second target weighted score sequence in the plurality of alternative providers to obtain a fourth difference coefficient corresponding to each alternative provider; and finally, determining the comprehensive scores corresponding to the alternative suppliers based on the third difference coefficient corresponding to each alternative supplier and the fourth difference coefficient corresponding to each alternative supplier so as to select the supplier from a plurality of alternative suppliers based on the comprehensive scores corresponding to the alternative suppliers. Therefore, the method and the device can comprehensively score each alternative supplier from the two dimensions of the first scoring index related to the product quality and the second scoring index related to the product cost, so that the alternative suppliers with high product quality and low product cost correspond to higher comprehensive scores, and the high-quality suppliers can be determined from the two dimensions of the product quality and the product finished product.
In a second aspect, referring to fig. 2, an embodiment of the present application provides a cloud digital supply chain management method, which is applied to a cloud server, and the method includes the following steps S201 to S207.
Step S201, a first scoring index sequence which is uploaded by a user terminal and is related to product quality of a plurality of alternative suppliers and a second scoring index sequence which is uploaded by the plurality of alternative suppliers and is related to product cost are received, wherein the first scoring index sequence comprises at least one type of first scoring index, and the second scoring index sequence comprises at least one type of second scoring index.
Step S202, determining a first difference coefficient of each type of first scoring index and a second difference coefficient of each type of second scoring index based on a first scoring index sequence corresponding to a plurality of alternative suppliers and a second scoring index sequence corresponding to the plurality of alternative suppliers.
S203, determining a first weight corresponding to each type of first scoring index and a second weight corresponding to each type of second scoring index based on the first difference coefficient of each type of first scoring index and the second difference coefficient of each type of second scoring index.
Step S204, determining a first weighted scoring sequence corresponding to each alternative provider in the plurality of alternative providers and a second weighted scoring sequence corresponding to each alternative provider in the plurality of alternative providers based on the first weights corresponding to the various first scoring indexes and the second weights corresponding to the various second scoring indexes.
Step S205, selecting the maximum value of a plurality of first weighted scores corresponding to various first scoring indexes from the first weighted score sequences corresponding to a plurality of alternative suppliers to obtain a first target weighted score sequence, and selecting the minimum value of a plurality of second weighted scores corresponding to various second scoring indexes from the second weighted score sequences corresponding to a plurality of alternative suppliers to obtain a second target weighted score sequence.
S206, calculating the difference between the first weighted score sequence corresponding to each alternative provider and the first target weighted score sequence in the plurality of alternative providers to obtain a third difference coefficient corresponding to each alternative provider, and calculating the difference between the second weighted score sequence corresponding to each alternative provider and the second target weighted score sequence in the plurality of alternative providers to obtain a fourth difference coefficient corresponding to each alternative provider.
Step S207, determining comprehensive scores corresponding to the alternative suppliers based on the third difference coefficient corresponding to the alternative suppliers and the fourth difference coefficient corresponding to the alternative suppliers, so as to select the suppliers from the alternative suppliers based on the comprehensive scores corresponding to the alternative suppliers.
The working process, working details and technical effects of the method provided in the second aspect of the present embodiment may be referred to in the first aspect of the present embodiment, and are not described herein.
Finally, it should be noted that: the foregoing description is only of the preferred embodiments of the invention and is not intended to limit the scope of the invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A cloud digital supply chain management system, comprising: the cloud terminal comprises a user terminal and a cloud server, wherein the user terminal is in communication connection with the cloud server;
the user terminal is used for uploading first scoring index sequences of a plurality of alternative suppliers and related to product quality and second scoring index sequences of the plurality of alternative suppliers and related to product cost to the cloud server, wherein the first scoring index sequences comprise at least one type of first scoring index, and the second scoring index sequences comprise at least one type of second scoring index;
the cloud server is used for determining a first difference coefficient of each type of first scoring index and a second difference coefficient of each type of second scoring index based on the first scoring index sequences corresponding to the plurality of alternative suppliers and the second scoring index sequences corresponding to the plurality of alternative suppliers;
The cloud server is further used for determining first weights corresponding to the first scoring indexes and second weights corresponding to the second scoring indexes based on the first difference coefficients of the first scoring indexes and the second difference coefficients of the second scoring indexes;
the cloud server is further configured to determine a first weighted score sequence corresponding to each alternative provider of the plurality of alternative providers and a second weighted score sequence corresponding to each alternative provider of the plurality of alternative providers based on a first weight corresponding to each type of first score index and a second weight corresponding to each type of second score index;
the cloud server is further configured to select a maximum value of a plurality of first weighted scores corresponding to each type of first score index from the first weighted score sequences corresponding to the plurality of alternative suppliers, obtain a first target weighted score sequence, and select a minimum value of a plurality of second weighted scores corresponding to each type of second score index from the second weighted score sequences corresponding to the plurality of alternative suppliers, obtain a second target weighted score sequence;
the cloud server is further configured to calculate a difference between a first weighted score sequence corresponding to each candidate provider and the first target weighted score sequence in the plurality of candidate providers, obtain a third difference coefficient corresponding to each candidate provider, and calculate a difference between a second weighted score sequence corresponding to each candidate provider and the second target weighted score sequence in the plurality of candidate providers, obtain a fourth difference coefficient corresponding to each candidate provider;
The cloud server is further configured to determine a composite score corresponding to each candidate provider based on the third difference coefficient corresponding to each candidate provider and the fourth difference coefficient corresponding to each candidate provider, so as to select a provider from the plurality of candidate providers based on the composite score corresponding to each candidate provider.
2. The cloud digital supply chain management system of claim 1, wherein the cloud server is configured to, when determining the first difference coefficient of each type of first scoring index and the second difference coefficient of each type of second scoring index based on the first scoring index sequences corresponding to the plurality of alternative suppliers and the second scoring index sequences corresponding to the plurality of alternative suppliers, specifically:
establishing a first scoring index matrix and a second scoring index matrix corresponding to the multiple alternative suppliers according to a first scoring index sequence corresponding to the multiple alternative suppliers and a second scoring index sequence corresponding to the multiple alternative suppliers, wherein each row of the first scoring index matrix corresponds to the first scoring index sequence of one alternative supplier, each row of the second scoring index matrix corresponds to the second scoring index sequence of one alternative supplier, each column of the first scoring index matrix corresponds to multiple first scoring indexes which are in the same type and are in one-to-one correspondence with the multiple alternative suppliers, and each column of the second scoring index matrix corresponds to multiple second scoring indexes which are in the same type and are in one-to-one correspondence with the multiple alternative suppliers;
Calculating the information entropy of each type of first scoring index in the first scoring index matrix and the information entropy of each type of second scoring index in the second scoring index matrix;
and determining the difference degree of each type of first scoring index based on the information entropy of each type of first scoring index in the first scoring index matrix, and determining the difference degree of each type of second scoring index based on the information entropy of each type of second scoring index in the second scoring index matrix.
3. The cloud digital supply chain management system of claim 2, wherein the cloud server, prior to being configured to calculate the information entropy of each type of first scoring indicator in the first scoring indicator matrix and the information entropy of each type of second scoring indicator in the second scoring indicator matrix, is further configured to:
and normalizing the first scoring index matrix and the second scoring index matrix corresponding to the plurality of alternative suppliers.
4. The cloud digital supply chain management system according to claim 1, wherein the cloud server is configured to, when determining the first weights corresponding to the first scoring indexes and the second weights corresponding to the second scoring indexes based on the first difference coefficients of the first scoring indexes and the second difference coefficients of the second scoring indexes, specifically:
Determining a first weight which corresponds to each type of first scoring index and is positively correlated with the difference degree based on the difference degree of each type of first scoring index;
and determining second weights which correspond to the second scoring indexes and are positively correlated with the difference degrees based on the difference degrees of the second scoring indexes.
5. The cloud digital supply chain management system of claim 1, wherein the cloud server is configured to, when calculating a difference between a first weighted score sequence corresponding to each of the plurality of candidate suppliers and the first target weighted score sequence to obtain a third difference coefficient corresponding to each of the candidate suppliers, and calculating a difference between a second weighted score sequence corresponding to each of the plurality of candidate suppliers and the second target weighted score sequence to obtain a fourth difference coefficient corresponding to each of the candidate suppliers:
respectively converting a first weighted scoring sequence and a second weighted scoring sequence corresponding to each alternative provider in the plurality of alternative providers into vectors to obtain a first vector and a second vector corresponding to each alternative provider;
respectively converting the first target weighted scoring sequence and the second target weighted scoring sequence into vectors to obtain a third vector and a fourth vector;
Calculating Euclidean distance between the first vector corresponding to each alternative provider and the third vector to obtain a third difference coefficient corresponding to each alternative provider;
and calculating Euclidean distance between the second vector corresponding to each alternative provider and the fourth vector to obtain a fourth difference coefficient corresponding to each alternative provider.
6. The cloud digital supply chain management system according to claim 1, wherein the cloud server is configured to, when determining the composite score corresponding to each candidate provider based on the third difference coefficient corresponding to each candidate provider and the fourth difference coefficient corresponding to each candidate provider, specifically:
and calculating the comprehensive score corresponding to each alternative provider through a TOPSIS algorithm based on the third difference coefficient corresponding to each alternative provider and the fourth difference coefficient corresponding to each alternative provider.
7. The cloud digital supply chain management system of claim 1, wherein the first scoring index sequence comprises a product quality index and/or an after-market service index and the second scoring index sequence comprises a price index and/or a logistic cost index.
8. The cloud digital supply chain management system of claim 1, wherein the cloud server is further configured to rank the plurality of candidate suppliers based on the composite score corresponding to each candidate supplier, and send the ranking result to the user terminal.
9. The cloud digital supply chain management system according to claim 8, wherein the cloud server is configured to, when configured to send the ranking result to the user terminal:
and sending a plurality of alternative suppliers which are ranked ahead in the ranking result to the user terminal.
10. The cloud digital supply chain management method is applied to a cloud server and is characterized by comprising the following steps:
receiving a first scoring index sequence which is uploaded by a user terminal and is related to the product quality of a plurality of alternative suppliers and a second scoring index sequence which is uploaded by the user terminal and is related to the product cost of the plurality of alternative suppliers, wherein the first scoring index sequence comprises at least one type of first scoring index, and the second scoring index sequence comprises at least one type of second scoring index;
determining a first difference coefficient of each type of first scoring index and a second difference coefficient of each type of second scoring index based on the first scoring index sequences corresponding to the plurality of alternative suppliers and the second scoring index sequences corresponding to the plurality of alternative suppliers;
Determining a first weight corresponding to each type of first scoring index and a second weight corresponding to each type of second scoring index based on the first difference coefficient of each type of first scoring index and the second difference coefficient of each type of second scoring index;
determining a first weighted scoring sequence corresponding to each alternative provider of the plurality of alternative providers and a second weighted scoring sequence corresponding to each alternative provider of the plurality of alternative providers based on the first weights corresponding to the various first scoring indexes and the second weights corresponding to the various second scoring indexes;
selecting the maximum value of a plurality of first weighted scores corresponding to various first scoring indexes from the first weighted score sequences corresponding to the plurality of alternative suppliers to obtain a first target weighted score sequence, and selecting the minimum value of a plurality of second weighted scores corresponding to various second scoring indexes from the second weighted score sequences corresponding to the plurality of alternative suppliers to obtain a second target weighted score sequence;
calculating the difference between the first weighted score sequence corresponding to each alternative provider and the first target weighted score sequence in the plurality of alternative providers to obtain a third difference coefficient corresponding to each alternative provider, and calculating the difference between the second weighted score sequence corresponding to each alternative provider and the second target weighted score sequence in the plurality of alternative providers to obtain a fourth difference coefficient corresponding to each alternative provider;
And determining comprehensive scores corresponding to the alternative suppliers based on the third difference coefficient corresponding to the alternative suppliers and the fourth difference coefficient corresponding to the alternative suppliers, so as to select the supplier from the alternative suppliers based on the comprehensive scores corresponding to the alternative suppliers.
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