Power transmission and transformation project emergency material supplier selection evaluation method

Abstract

The invention provides a power transmission and transformation project emergency material supplier selection evaluation method, which is characterized in that related factors of each material supplier are collected, and evaluation indexes of emergency material suppliers are constructed on the basis of comprehensive analysis and actual research; constructing a cost evaluation model, listing a basic decision matrix, and performing standardized calculation on the basic decision matrix to obtain a standardized decision matrix; obtaining a combined weight vector of the evaluation indexes based on a combined weighting method, and carrying out weighted calculation on the standardized decision matrix to obtain a weighted decision matrix; based on a COPRAS method, calculating to obtain a comprehensive evaluation value and effectiveness of each emergency material supplier; and evaluating the obtained comprehensive evaluation value and effectiveness, and determining an optimal emergency material supplier. According to the method, objective and comprehensive cost evaluation and comparison can be carried out on each emergency material supplier, the emergency material suppliers are reasonably selected, a modern emergency guarantee mode is constructed, and an optimal emergency material supplier selection strategy is given.

Description

Technical Field

[0001] The present invention relates to the technical field of power transmission and transformation project construction risk management, and in particular to a method for selecting and evaluating suppliers of emergency materials for power transmission and transformation projects. Background Art

[0002] my country's power transmission and transformation projects are in a period of vigorous development. Economic and social issues are closely linked, historical and current issues influence each other, and traditional and non-traditional security threats interact with each other. The tasks of management departments at all levels to respond to emergencies and natural disasters are becoming increasingly arduous. Organizing and implementing efficient emergency material management is an important link for all departments to respond to new challenges and build a modern emergency support model. At the same time, due to the large variety, large quantity, high value, wide distribution and difficulty in management of emergency materials, how to ensure that the principles of openness, fairness and justice are maintained in the procurement of emergency materials, and how to reasonably select emergency material suppliers are issues worthy of in-depth study.

[0003] As the core hub of the power system, power transmission and transformation projects have the characteristics of wide impact, tight timeliness, and complex technology in their sudden failures. The selection of emergency material suppliers is directly related to the efficiency of emergency repairs and the safety of the power grid. High-quality suppliers must have rapid response capabilities (such as 24-hour material allocation), strict quality assurance (in compliance with power equipment certification standards) and supply chain resilience (multi-location warehousing and flexible logistics) to cope with uncertainties under extreme events. Therefore, the scientific and reasonable determination of evaluation index weights has an important impact on supplier selection. The application of the COPRAS method to the selection of emergency material suppliers for power transmission and transformation projects uses a single weighting method to determine the index weights, which leads to inaccurate evaluation results. Summary of the invention

[0004] The purpose of the present invention is to provide a method for selecting and evaluating emergency material suppliers for power transmission and transformation projects, which can objectively and comprehensively evaluate and compare the costs of various emergency material suppliers, reasonably select emergency material suppliers, build a modern emergency guarantee model, and provide the best emergency material supplier selection strategy. In order to achieve the above technical features, the purpose of the present invention is achieved as follows:

[0005] A method for selecting and evaluating suppliers of emergency materials for power transmission and transformation projects, comprising:

[0006] Collect relevant factors of each material supplier, and build evaluation indicators for emergency material suppliers based on comprehensive analysis and actual research;

[0007] Construct a cost assessment model, list the basic decision matrix, perform standardized calculations on the basic decision matrix, and obtain a standardized decision matrix;

[0008] Based on the combined weighting method, the combined weight vector of the evaluation indicators is obtained, and the weighted calculation of the standardized decision matrix is carried out to obtain the weighted decision matrix;

[0009] Based on the COPRAS method, the comprehensive evaluation values and utility degrees of each emergency material supplier are calculated; the obtained comprehensive evaluation values and utility degrees are evaluated to determine the optimal emergency material supplier.

[0010] The relevant factors of the material supplier include the price of the supplied products, supply capacity, delivery time and product quality.

[0011] Suppose the emergency management department wants to evaluate m emergency material suppliers, and the set composed of emergency material suppliers is denoted as A = {A1, A2,..., A m}; there are n evaluation indicators for each emergency material supplier, and the indicator set is denoted as C = {C1, C2,..., C n}. Under different indicators, each supplier is evaluated, and the obtained decision matrix is denoted as:

[0012]

[0013] where: x ij is the evaluation value of the i-th emergency material supplier under the indicator C j .

[0014] The basic decision matrix is standardized to obtain the standardized decision matrix:

[0015]

[0016] The weights of the evaluation indicators are determined by the combined weighting method. The subjective and objective weights are directly combined mathematically. The game theory combined weighting method regards the subjective and objective weighting as two sides of the game, making the weights conform to expert experience and fit the data law, making the weight coefficients more scientific and reasonable.

[0017] On the basis of calculating the weighted decision matrix, the combined weights of the evaluation indicators are obtained based on the combined weighting method, and the weighted calculation of the standardized decision matrix is carried out to obtain the weighted decision matrix.

[0018] After obtaining the weighted decision matrix, the COPRAS method is used to calculate the comprehensive evaluation values and utility degrees of each emergency material supplier, and the obtained comprehensive evaluation values and utility degrees are evaluated to determine the optimal emergency material supplier.

[0019] The value range of the utility degree of each emergency material supplier is between 0 and 100%, and the utility degree of the optimal emergency material supplier is 100%.

[0020] In the process of selecting emergency material suppliers, the best emergency material supplier selection strategy should be determined by combining the ranking of the comprehensive evaluation value Qi and the maximum supply capacity of each emergency material supplier.

[0021] It also includes integrating the steps of obtaining risk evaluation results to construct an evaluation model for selecting emergency material suppliers for power transmission and transformation projects.

[0022] The present invention has the following beneficial effects:

[0023] 1. Aiming at the problem of evaluating and selecting emergency material suppliers for power transmission and transformation projects, through in-depth analysis of various relevant factors of emergency material suppliers for power transmission and transformation projects, four factors including product price, supply capacity, delivery time and product quality are selected as evaluation indicators for emergency material suppliers, so as to further achieve comprehensive and multi-faceted evaluation, and keep the calculation amount reasonable and scientific, and can objectively and comprehensively evaluate and compare the costs of each emergency material supplier, and give the best emergency material supplier selection strategy in the reasonable selection of emergency material suppliers and the construction of modern emergency support models;

[0024] 2. Through the game theory combined weighting method of FAHP-CRITIC, the comprehensive weights of each index are determined to ensure the scientificity and objectivity of the index weights, and the weighted calculation of the standardized decision matrix is carried out to obtain a weighted decision matrix that better conforms to objective conditions as the basis for further evaluation and analysis calculations;

[0025] 3. Using the COPRAS method, an evaluation model for selecting emergency material suppliers for power transmission and transformation projects is constructed. Based on the collected relevant factors, a basic decision matrix is listed to facilitate comparative data calculation and analysis, and the standardized calculation of the decision matrix is carried out to realize the comparison conditions of multiple emergency material suppliers for power transmission and transformation projects;

[0026] 4. According to the comprehensive evaluation value and utility degree calculated from the weighted decision matrix, the multi-attribute analysis method is used for the comprehensive evaluation value and utility degree to realize the comprehensive evaluation, quantitative analysis and comparison of the selection of each emergency material supplier for power transmission and transformation projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The present invention will be further described below with reference to the drawings and embodiments.

[0028] Figure 1 It is a flow chart of a method for evaluating and selecting emergency material suppliers for power transmission and transformation projects provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0029] The embodiments of the present invention will be further described below with reference to the drawings.

[0030] In order to provide a scientific and reasonable decision-making basis for the selection of emergency material suppliers for power transmission and transformation projects, promote the principle of openness, fairness, and impartiality in the selection of emergency material suppliers for power transmission and transformation projects, and reasonably select emergency material suppliers, the present invention combines the game theory combined weighting method of FAHP-CRITIC and the multi-attribute decision-making method COPRAS method, collects relevant factors of each material supplier, selects four factors including product price, supply capacity, delivery time, and product quality provided by the emergency material supplier as evaluation indicators for the emergency material supplier, and proposes a comprehensive multi-attribute decision-making evaluation model, calculates the weight of each indicator factor, obtains quantitative evaluation data, and realizes the scientificity and comprehensiveness of the evaluation of the selection of emergency material suppliers for power transmission and transformation projects.

[0031] Such as Figure 1 , the present invention provides a specific example implementation of a method for evaluating the selection of emergency material suppliers for power transmission and transformation projects, and the steps include:

[0032] S1: Collect relevant factors of each material supplier, and select four factors including product price, supply capacity, delivery time, and product quality provided by the emergency material supplier as evaluation indicators for the emergency material supplier;

[0033] S2: Construct a cost evaluation model, list the basic decision matrix; perform standardized calculation of the basic decision matrix to obtain a standardized decision matrix;

[0034] S3: Obtain the combined weight vector of the evaluation indicators based on the game theory combined weighting method of FAHP-CRITIC method, and perform weighted calculation of the standardized decision matrix to obtain a weighted decision matrix;

[0035] S4: Calculate the comprehensive evaluation value and utility degree of each emergency material supplier; evaluate the obtained comprehensive evaluation value and utility degree, and determine the optimal emergency material supplier.

[0036] Based on the above embodiments, for the evaluation problem of the selection of emergency material suppliers for power transmission and transformation projects, a method for evaluating the selection of emergency material suppliers for power transmission and transformation projects is provided. Four factors including product price, supply capacity, delivery time, and product quality are selected as evaluation indicators for the emergency material supplier. A cost evaluation model is constructed, the basic decision matrix is listed, the standardized calculation of the basic decision matrix is performed to obtain a standardized decision matrix, the combined weight of the indicators is calculated, the weighted calculation of the standardized decision matrix is performed to obtain a weighted decision matrix, and the comprehensive evaluation value and utility degree calculated according to the weighted decision matrix. During the evaluation process, the comprehensive weight of the evaluation indicators is determined by the game theory combined weighting method of FAHP-CRITIC method, and the comprehensive evaluation value and utility degree are compared and analyzed to realize the evaluation, analysis and comparison of the selection of emergency material suppliers for power transmission and transformation projects, and ensure the scientificity and comprehensiveness of the indicator weights.

[0037] In the process of constructing the basic decision matrix, it is assumed that the emergency management department wants to evaluate m emergency material suppliers, and the set composed of emergency material suppliers is denoted as A = {A1, A2,..., A m}; there are n indicators for evaluating each emergency material supplier, and the indicator set is denoted as C = {C1, C2,..., C n}. Under different indicators, each supplier is evaluated, and the obtained decision matrix is denoted as

[0038]

[0039] where: x ij is the evaluation value of the i-th emergency material supplier under the indicator C j . For the emergency material supplier A i , if C j ∈ J1, the larger the value of x ij , the better the supplier; on the contrary, if C j ∈ J1, the larger the value of x ij , the worse the supplier.

[0040] The basic decision matrix is standardized to obtain the standardized decision matrix,

[0041]

[0042] The weights of the evaluation indicators include subjective weights and objective weights; the subjective weights adopt the FAHP method, the objective weights adopt the CRITIC method, and the subjective weight method adopts the FAHP method, and the combined weights are calculated by the game theory combined weighting method.

[0043] The specific steps of the FAHP method are as follows:

[0044] S1: Determine the fuzzy judgment matrix. The fuzzy judgment matrix represents the comparison of the relative importance between two layers of elements. Assuming that there is a connection between the upper and lower layers of elements, the fuzzy judgment matrix F can be expressed as

[0045]

[0046] In order to characterize the relative importance degree, the 0.1 - 0.9 scale method is adopted, and the larger the value, the relatively more important. The importance of two elements in the same layer of indicators compared with each other for the associated indicator in the upper layer is quantitatively described (see Table 1).

[0047] Table 1 Quantitative scale

[0048]

[0049] S2: Convert the fuzzy judgment matrix into a fuzzy consistent matrix through Equations (5) and (6), and it can be expressed as

[0050]

[0051] S3: Calculate the weights of each index. The calculation formula for the weight wj is:

[0052]

[0053] In the formula, a is the importance difference factor, and the value range is a ≥ (n - 1) / 2.

[0054] The specific steps of the CRITIC method are as follows:

[0055] S1: Construct the samples to be evaluated. Assume there are m samples to be evaluated and n evaluation indexes, and establish the initial index data matrix; 2) Data standardization. To eliminate the influence of different index dimensions on the results, the data is dimensionless processed to obtain the standardized matrix; 3) Calculate the information carrying capacity. The volatility S of the data j can be expressed as:

[0056]

[0057] In the formula: is the mean value of each index; b i ' j represents the data after standardization.

[0058] S2: Calculate the conflict matrix R and the information amount Cj of the indexes. The calculation formulas are:

[0059]

[0060] In the formula, r ij represents the element in the i-th row and j-th column of the conflict matrix R.

[0061] The conflict A of the data j and the information carrying capacity C j are expressed as

[0062]

[0063] C j = S j × A j ; (12)

[0064] S3: Calculate the weight wj'

[0065]

[0066] The main steps of calculating the comprehensive weight by the game theory combined weighting method are as follows:

[0067] S1: Construct the linear combination \(W\) of subjective and objective weights. Construct the basic weight vector set. For \(n\) indicators, use two methods of subjective and objective weight assignment to obtain the weight set \(W = \{\omega_1,\omega_2\}\). Then any linear combination \(W\) of these two groups of vectors is:

[0068]

[0069] where \(a_1\) and \(a_2\) are the subjective and objective weight combination coefficients respectively.

[0070] S2: Optimize the combination coefficients. According to the idea of the game theory model, optimize the combination coefficients \(a_1\) and \(a_2\) to seek the best linear weights. The optimization objective function is based on minimizing the deviation. The specific form is shown in Equation (15):

[0071] \(\min||W - w k ||^2,k = 1,2,\cdots,n;(15)

[0072] S3: Solve the optimal combination coefficients. According to the matrix differential property, transform the above optimization problem into a system of linear differential equations for the first-order derivative conditions of optimization, as shown in Equation (16):

[0073]

[0074] S4: Determine the optimal combination weight based on game theory. According to the obtained optimal linear combination coefficients \(a_1\) and \(a_2\), perform normalization processing to obtain the comprehensive weight vector \(W\) based on game theory weight assignment, as shown in Equation (17):

[0075]

[0076] Combined with the weights of the emergency material supplier evaluation indicators given by Equation (17), the evaluation process of emergency material suppliers based on the COPRAS method is as follows:

[0077] Combined with the normalized decision matrix in Equation (3), calculate the weighted normalized decision matrix \(R=(r ij ) m×n .

[0078] r ij = y ij \times w j i = 1,2,\cdots,n;(18)

[0079] For the benefit indicators of the emergency material supplier \(A_i\) in the power transmission and transformation project, determine its comprehensive benefit value through Equation (18) value

[0080]

[0081] where: Obviously, The larger the value, the better the solution Ai.

[0082] For the benefit index of the emergency material supplier Ai in the power transmission and transformation project, its comprehensive cost value is determined by formula (20). The value of

[0083]

[0084] In the formula: Obviously, The smaller the value, the better the solution Ai.

[0085] For each emergency material supplier Ai, its comprehensive evaluation value is calculated by formula (21).

[0086]

[0087] In the formula: Obviously, the larger the value of Qi, the better the emergency material supplier Ai. If a certain emergency material supplier has the largest comprehensive evaluation value Qi, then this emergency material supplier should be the best choice.

[0088] Finally, the utility degree of each emergency material supplier is calculated by formula (22).

[0089]

[0090] In the formula:

[0091] The value range of the utility degree of each emergency material supplier is between 0 and 100%. The utility degree of the optimal emergency material supplier is 100%. In the process of selecting emergency material suppliers, the best emergency material supplier selection strategy should be determined by combining the ranking of Qi and the maximum supply capacity of each emergency material supplier. The specific process is as follows: First, sort each Ui from large to small, which may be denoted as U(1)≥U(2)≥…≥U(m). This order is the preferred selection order of emergency material suppliers, that is, the supplier corresponding to U(1) is considered first. If the supplier corresponding to U(1) meets the order quantity, the supplier corresponding to U(1) should be selected; if the supplier corresponding to U(1) cannot meet the order quantity, the suppliers corresponding to U(1) and U(2) should be selected, that is, order from the supplier corresponding to U(1) according to its maximum supply capacity first, and then order the remaining quantity from the supplier corresponding to U(2); and so on, the best emergency material supplier selection strategy can be obtained.

[0092] Specific implementation case:

[0093] Suppose an emergency material reserve center for a power transmission and transformation project needs to purchase an emergency material. After preliminary screening, it is necessary to evaluate 10 emergency material suppliers and determine the best emergency material supplier selection strategy. The set composed of the corresponding 10 emergency material suppliers is denoted as A = {A1, A2,..., A 10}. Each emergency material supplier is evaluated in combination with the given 4 indicators: product price (C1), supply capacity (C2), delivery time (C3), and product quality (C4). Among them, supply capacity and product quality are benefit-type indicators, that is, J1 = {C2, C4}; product price and delivery time are cost-type indicators, that is, J2 = {C1, C3}. The evaluation values of each emergency material supplier under different evaluation indicators are shown in Table 2.

[0094] Table 2 Evaluation values of each emergency material supplier under different indicators

[0095]

[0096]

[0097] The normalization processing of the emergency material supplier selection indicators in the above table is carried out using Equation (2) to obtain the following normalized decision matrix

[0098]

[0099] The fuzzy analytic hierarchy process is used to determine the index weights. To make the scoring scientific and objective, 6 experts are invited to score, and their average value is taken as the fuzzy judgment matrix, which can be expressed as:

[0100]

[0101] According to Equations (5) and (6), the fuzzy consistent matrix R is calculated as:

[0102]

[0103] Finally, the subjective weights are calculated according to Equation (8) as:

[0104] w1 = 0.3, w2 = 0.24, w3 = 0.25, w4 = 0.21

[0105] According to the consistency test, the CR index is 0.0774 < 0.1, and the consistency test is passed.

[0106] The objective weights are calculated using the CRITIC method. According to Equations (8)-(13), the objective weights of each index are:

[0107] w1 = 0.1746, w2 = 0.3540, w3 = 0.4033, w4 = 0.0681

[0108] To avoid the weight imbalance caused by a single type of empowerment method, the present invention adopts a game theory combined empowerment method to obtain a weight combination with a balance of subjectivity and objectivity, and the calculation is as follows:

[0109]

[0110] According to the calculation of formula (16), a1 = 0.32121 and a2 = 0.68255 can be obtained. According to the calculation of formula (17), the final a1 and a2 are:

[0111]

[0112] Finally, the final weights calculated by game theory are shown in Table 3:

[0113] Table 3 Final combined weights of evaluation indicators

[0114] Evaluation index FAHP subjective weighting CRITIC objective weighting Comprehensive weight Product price 0.30 0.1746 0.2147 Supply capacity 0.24 0.3540 0.3181 Delivery time 0.25 0.4033 0.3542 Product quality 0.21 0.0681 0.1130

[0115] The weighted normalized matrix is calculated from formula (18) as:

[0116]

[0117] For effectiveness indicators, formula (19) is used to calculate their comprehensive effectiveness values. For cost-type indicators (20), their comprehensive cost values are calculated. The comprehensive evaluation value is calculated through formula (21), and finally the utility degree of each emergency material supplier is calculated according to formula (22). The results are shown in Table 4 below:

[0118] Table 4 Comprehensive evaluation of emergency material suppliers

[0119] Comprehensive effect value Comprehensive cost value Comprehensive evaluation value Utilization degree <![CDATA[A1]]> 0.0305 0.0490 0.0923 0.0923 <![CDATA[A2]]> 0.0411 0.0821 0.0780 0.0780 <![CDATA[A3]]> 0.0346 0.0745 0.0752 0.0752 <![CDATA[A4]]> 0.0255 0.0412 0.0990 0.0990 <![CDATA[A5]]> 0.0442 0.0417 0.1169 0.1169 <![CDATA[A6]]> 0.0523 0.0482 0.1152 0.1152 <![CDATA[A7]]> 0.0482 0.0506 0.1080 0.1080 <![CDATA[A8]]> 0.0352 0.0443 0.1036 0.1036 <![CDATA[A9]]> 0.0596 0.0823 0.0964 0.0964 <![CDATA[A 10 > 0.0601 0.0549 0.1153 0.1153

[0120] As can be seen from the above table, the order of their effectiveness degrees is A5 > A10 > A6 > A7 > A8 > A4 > A9 > A1 > A2 > A3. Therefore, in the actual selection process, it is necessary to analyze in combination with the order of their effectiveness degrees and the actual supply capabilities of each emergency material supplier. It can be seen from Table 2 that the maximum supply capabilities of emergency material suppliers A5, A10, A6, A7, A8, A4, A9, A1, A2, and A3 are 700, 1000, 900, 800, 500, 300, 1000, 400, 600, and 500 respectively.Suppose the demand for the emergency material reserve warehouse is \(x\) pieces. If \(x \lt 700\), the emergency material reserve center only selects emergency material supplier A5, that is, directly orders \(x\) pieces from supplier A5. If the demand for the emergency material reserve warehouse is \(700 \lt x \lt 1700\) pieces, the emergency material reserve center only selects emergency material suppliers A5 and A10, that is, directly orders 700 pieces from supplier A5 and the remaining \(x - 1700\) from supplier A10. If the demand for the emergency material reserve warehouse is \(1700 \lt x \lt 2600\) pieces, the emergency material reserve center only selects emergency material suppliers A5, A10 and A6, that is, directly orders 700 pieces from supplier A5, 1000 pieces from supplier A10, and the remaining \(x - 1700\) from supplier A6. If the demand for the emergency material reserve warehouse is \(2600 \lt x \lt 3400\) pieces, the emergency material reserve center only selects emergency material suppliers A5, A10, A6 and A7, that is, directly orders 700 pieces from supplier A5, 1000 pieces from supplier A10, 900 pieces from supplier A6, and the remaining \(x - 2600\) from supplier A7. If the demand for the emergency material reserve warehouse is \(3400 \lt x \lt 3900\) pieces, the emergency material reserve center only selects emergency material suppliers A5, A10, A6, A7 and A8, that is, directly orders 700 pieces from supplier A5, 1000 pieces from supplier A10, 900 pieces from supplier A6, 800 pieces from supplier A7, and the remaining \(x - 3400\) from supplier A8. If the demand for the emergency material reserve warehouse is \(3900 \lt x \lt 4200\) pieces, the emergency material reserve center only selects emergency material suppliers A5, A10, A6, A7, A8, A4 and A9, that is, directly orders 700 pieces from supplier A5, 1000 pieces from supplier A10, 900 pieces from supplier A6, 800 pieces from supplier A7, 300 pieces from supplier A7, 500 pieces from supplier A8, and the remaining \(x - 4200\) from supplier A4. If the demand for the emergency material reserve warehouse is \(4200 \lt x \lt 5200\) pieces, the emergency material reserve center only selects emergency material suppliers A5, A10, A6, A7, A8, A4 and A9, that is, directly orders 700 pieces from supplier A5, 1000 pieces from supplier A10, 900 pieces from supplier A6, 800 pieces from supplier A7, 300 pieces from supplier A7, 300 pieces from supplier A4, and the remaining \(x - 4200\) from supplier A9. And so on, the optimal emergency material supplier selection strategy can be determined. The optimal emergency material supplier selection strategy for this problem is shown in Table 5.

[0121] Table 5 Selection order and order quantity of emergency material suppliers

[0122]

[0123] In this case, the product price of emergency supplies supplier A5 is relatively high, but it is the best choice. The main reasons are that this emergency supplies supplier has the shortest delivery time, as well as good product supply capacity and product quality. Similarly, the product price of emergency supplies supplier A10 is relatively high, but it is the second-best choice. The main reasons are that this emergency supplies supplier has the best product quality, the largest supply capacity, and a relatively reasonable delivery time. And delivery time and the largest supply capacity carry a high weight in the issue of selecting emergency supplies suppliers.

Claims

1. A method for selecting and evaluating emergency material suppliers for power transmission and transformation projects, characterized in that, Including: Collect relevant factors of each material supplier, and construct evaluation indicators for emergency material suppliers based on comprehensive analysis and actual investigation; Construct a cost evaluation model, list the basic decision matrix, and perform standardized calculation of the basic decision matrix to obtain the standardized decision matrix; Based on the combined weighting method, obtain the combined weight vector of the evaluation indicators, and perform weighted calculation of the standardized decision matrix to obtain the weighted decision matrix; Based on the COPRAS method, calculate the comprehensive evaluation value and utility degree of each emergency material supplier; evaluate the obtained comprehensive evaluation value and utility degree to determine the optimal emergency material supplier.

2. The evaluation method for selecting emergency material suppliers in power transmission and transformation projects according to claim 1, characterized in that: The relevant factors of the material supplier include the price of the supplied product, supply capacity, delivery time, and product quality.

3. The evaluation method for selecting emergency material suppliers in power transmission and transformation projects according to claim 2, wherein: Suppose the emergency management department wants to evaluate m emergency material suppliers, and the set composed of emergency material suppliers is denoted as A = {A1, A2,..., A m}; there are n indicators for evaluating each emergency material supplier, and the indicator set is denoted as C = {C1, C2,..., C n}. When evaluating each supplier under different indicators, the obtained decision matrix is denoted as: Where: x ij is the evaluation value of the i-th emergency material supplier under the index C j ​ 4. The evaluation method for selecting emergency material suppliers in power transmission and transformation projects according to claim 3, wherein: The standardized decision matrix is obtained by performing standardized processing on the basic decision matrix:

5. The evaluation method for selecting emergency material suppliers in power transmission and transformation projects according to claim 4, characterized in that: Determine the weights of the evaluation indicators through the combined weighting method, directly perform mathematical combination on the subjective and objective weights. The game theory combined weighting method regards the subjective and objective weighting as two parties in the game, making the weights conform to expert experience and fit the data law, making the weight coefficients more scientific and reasonable.

6. The evaluation method for selecting emergency material suppliers in power transmission and transformation projects according to claim 5, wherein: On the basis of calculating the weighted decision matrix, obtain the combined weights of the evaluation indicators based on the combined weighting method, and perform weighted calculation of the standardized decision matrix to obtain the weighted decision matrix.

7. The evaluation method for selecting emergency material suppliers in power transmission and transformation projects according to claim 6, characterized in that: After obtaining the weighted decision matrix, use the COPRAS method to calculate the comprehensive evaluation value and utility degree of each emergency material supplier, evaluate the obtained comprehensive evaluation value and utility degree, and determine the optimal emergency material supplier.

8. The evaluation method for selecting emergency material suppliers in power transmission and transformation projects according to claim 7, characterized in that: The value range of the utility degree of each emergency material supplier is between 0 and 100%, and the utility degree of the optimal emergency material supplier is 100%.

9. The evaluation method for selecting emergency material suppliers in power transmission and transformation projects according to claim 8, wherein: In the process of selecting emergency material suppliers, the best emergency material supplier selection strategy should be determined by combining the ranking of the comprehensive evaluation value Qi and the maximum supply capacity of each emergency material supplier.

10. The evaluation method for selecting emergency material suppliers in power transmission and transformation projects according to claim 9 is characterized in that: It also includes integrating the steps of obtaining the risk evaluation results to construct an evaluation model for selecting emergency material suppliers for power transmission and transformation projects.

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