118 results about "TOPSIS" patented technology

The invention relates to a key node recognition method for a regional power grid, and the basic flow of the method comprises the steps: inputting a power system topological structure and electrical characteristic parameters; calculating the values of evaluation indexes of a node; obtaining a node importance evaluation decision making matrix according to the values of the evaluation indexes; generating a node importance evaluation decision making matrix of a standard regional power grid; giving consideration to a Gini coefficient and a Kendall correlation coefficient, and solving the objective weights of the indexes through a CRITIC method; and solving an evaluation result of the node importance through a TOPSIS method. According to the technical scheme of the invention, the method gives full consideration to the physical features of the network topological structure and the operation state parameters of the power grid. The method can achieve the better recognition of the key node of the power grid, avoids the subjectivity of manual determination of the weights, and enables an evaluation result to be more suitable for the actual operation conditions of the power grid.

The invention discloses a TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) model-based intelligent substation secondary equipment evaluation method. The method mainly comprises the following steps: (1) acquiring characteristic sample indexes of each secondary equipment of an intelligent substation; (2) constructing an initial matrix according to the characteristic sample indexes of each secondary equipment and further obtaining a standardized decision making matrix by using a vector standardization method; (3) determining a weight value matrix and performing point multiplication on the weight value matrix and the standardized matrix to obtain a standardized weight decision making matrix; (4) determining a positive ideal solution vector and a negative ideal solution vector, and calculating the relative similarity degree of an evaluation index and the positive ideal solution of each evaluation object; (5) obtaining the state level of each secondary equipment, then determining a weight value of each secondary equipment, and finally obtaining a weighted comprehensive state level of the secondary equipment of the intelligent substation. By using the method, large sample data with multiple indexes and multiple evaluation objects of the intelligent substation can be considered, so that the operation status of the secondary equipment of the intelligent substation is more accurately evaluated.

The invention provides a TOPSIS-method multi-target threat ordering method based on information entropy. The method includes first building a threat assessment threat factor model, building a target attribute decision matrix according to the threat factor model, adopting an entropy weight method to calculate a target attribute weight vector according to the decision matrix, adopting a TOPSIS method to calculate relative close degree of target schemes according to the weight vector calculated through the entropy weight method and conducting threat assessment ordering on the schemes according to the close degree, namely the threat degree. By means of the method, shortcomings of the traditional ideal solution approaching ordering method in determination of weight coefficients are effectively overcome, and the target threat degree prediction accuracy is improved.

The invention relates to the technical field of charge management of vehicles, in particular to a method for orderly charging an electric vehicle based on TOPSIS sorting. The method includes the stepsof collecting electricity load information, parking lot information and electric vehicle index information in the residential area; monitoring the state of charging piles in a parking lot, and updating the number of available charging piles according to the current residential area load; judging whether the current time belongs to the charging time in the time strategy, setting the number of available charging piles to 0 If it is not a charging period, and sorting the charging sequence of the electric vehicle by the TOPSIS method If it is a charging period; outputting the orderly selection scheme of the current moment so that the charging piles work according to the selection result, and repeating the information collection step for circulation. The method for orderly charging the electric vehicle in the residential area based on the TOPSIS sorting can reasonably arrange the orderly charging of the electric vehicle while ensuring that the load in the residential area does not exceed the limitation, not only improves the completion rate of the charging and saves the charging cost, but also is conductive to an application of the electric vehicle charging in the residential area witha tight distribution power.

The invention provides a city agglomeration economy environment efficiency assessment method comprising the following steps: using a DEA model to measure the city agglomeration economy environment efficiency; using a DEA-SBM model considering unexpected output to parse the city agglomeration economy environment efficiency differences by taking environment pollutant as unexpected output restrictions; further using a TOPSIS model supported by entropy technology to parse the superposition relationship between resource investment, economic benefit, alleviation influence and ecology efficiency; finally using degree of relaxation analysis to obtain the city agglomeration economy environment efficiency difference reasons, and proposing corresponding countermeasures. An existing method mostly uses inter-provincial (zone) as a research object, yet the region development endoplasmic inhomogeneities problems cannot be clearly displayed by using the scaled data as indexes; the city agglomeration economy environment efficiency assessment method can solve said problems, and is suitable for city agglomeration economy environment efficiency assessment.

The invention belongs to the field of comprehensive electromagnetic compatibility evaluation, and particularly relates to a comprehensive electromagnetic compatibility evaluation method for a complicated electronic information system. The method is characterized by at least comprising the following steps of: 101, establishing an electromagnetic compatibility index system of a vehicle-mounted communication system; 102, acquiring original data of an index layer in the index system; 103, quantifying the original data of the index in the index layer; 104, acquiring an initial evaluation vector according to the quantified data corresponding to the indexes; 105, calculating a target weight vector for the index system according to an analytic network process (ANP) method; 106, performing performance concentration according to an improved TOPSIS method; and 107, analyzing an evaluation result. Positive and negative reference points are determined by a generalized reference point search method based on historical database sample statistics and replace ideal positive and negative points determined in a scheme to be evaluated by the conventional TOPSIS method; and furthermore, the close degree is calculated by a weighted euclidean distance, so that the problem that the evaluation result is reused is solved.

The invention relates to the technical field of electric system risk evaluation, in particular to an electric transmission line comprehensive risk evaluation method based on TOPSIS and optimal combination weight. The electric transmission line comprehensive risk evaluation method based on the TOPSIS and optimal combination weight overcomes the defects in the prior art, and the electric transmission line comprehensive risk evaluation method is perfected.

The invention provides a comprehensive risk priority number calculating method for architecture. Three risk factors (the appearance frequency, the severity degree and the discovery index) in FMEA are evaluated in the mode that fuzzy numbers are utilized in software architecture in a leveled mode; the appearance frequency and the discovery index are determined through component complexity and expertise, and the weights of different risk factors are distinguished through the conception of information entropy; through the conceptions of a positive ideal solution and a negative ideal solution in a TOPSIS method, a more reasonable and accurate risk priority number rank is obtained; in this way, a comprehensive software-failing mode risk factor evaluation technology for the architecture is achieved. By means of the comprehensive risk priority number calculating method, at the initial software design stage, developers are helped to find out potential design defects in a system, and therefore the subsequent software development quality is guaranteed.

The invention discloses a health safety state assessment device used for an electrical car. The health safety state assessment device comprises a signal acquisition and transmission system, a signal processing system and an execution system, wherein the signal acquisition and transmission system comprises a data acquisition module and a signal conversion module; an output end of the data acquisition module is connected with an input end of the signal conversion module; an output end of the signal conversion module is connected with an input end of the signal processing system; an output end of the signal processing module is connected with the execution system; the signal processing system comprises a micro processor; a software system in the micro processor comprises an expert module, a grey correlation module and a storage module; and a TOPSIS optimal seeking method and a pink correlation degree method are set in the grey correlation module. The health safety state assessment device can solve the technical problems that safety level of an existing electric car storage battery cannot be monitored and accessed very well.

The invention discloses a power grid planning risk evaluation system and method based on a grey correlation degree TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution). The power grid program risk evaluation system comprises a power grid planning data acquisition module, a power grid planning scheme input module and a controller, wherein the power grid planning data acquisition module and the power grid planning scheme input module are independently connected with the controller; and the controller comprises a power grid risk evaluation index matrix generation module, a power grid risk evaluation index matrix solving module, a grey correlation degree matrix construction module and a power grid planning scheme risk sorting module. The invention has the beneficial effects that the power grid planning risk evaluation system introduces the controller which can process power grid planning data and sort power planning schemes to carry out optimal sorting on power grid enterprise risk indexes, a power grid planning scheme can be evaluated on the whole, potential risks in a power grid planning process can be effectively prevented and solved, power grid planning operation cost is saved, and power grid reliability is improved.

The invention discloses a method for optimizing tunnel construction based on improved Topsis method which includes the following steps: step selection method, three-pilot method, middle pilot method,CRD method of main tunnel and annular excavation reserved core soil method of main tunnel are used in this paper. According to the five selected tunnel construction schemes, the following eight indexes are selected to establish the evaluation index system: surrounding rock engineering geological conditions, vault settlement, surface settlement, inverted arch uplift, Great Wall settlement, engineering progress, engineering cost and local inclination ratio of Great Wall. AHP method is used to determine the subjective weight Omega _ 1, information entropy method is used to determine the objective weight Omega _ 2, and game theory aggregation model is introduced to determine the comprehensive weight. The improved Topsis method is used to eliminate the calculation errors caused by different units. Grey relational grade is adopted to improve the sticking progress. On the basis of ensuring the safety of the Great Wall in the construction process, the invention selects a more reasonable construction method to maximize the engineering income.

The invention relates to a human health evaluation method based on a physiological health index, comprising the following steps: S1, measuring the human body to be evaluated, and obtaining actual measured values ​​of selected human body indexes; S2, normalizing the actual measured values ​​of each index processing to obtain the normalized value of each index; S3, assigning weights to each index; S4, determining the age and gender weight functions; S5, obtaining the LW index through linear weighting, and then obtaining the TOPSIS index by adjusting the TOPSIS model, and finally obtaining the index weighted Human body's physiological health LW&TOPSIS index. The present invention effectively fuses a plurality of physiological parameter index values ​​reflecting the health status of the human body, and gives the health evaluation result by the way of the human health index, which not only makes the evaluation result of the health status of the human body simpler and more intuitive, but also gives the evaluation result The results can enable non-professionals to clearly and clearly understand their own health status, and have important guiding significance for the adjustment of human body-related life activities and even the prevention and treatment of diseases.

The invention belongs to the technical field of system performance evaluation, and discloses a system performance comprehensive evaluation method, which comprises the steps of establishing a comprehensive evaluation hierarchical model of system performance, the comprehensive evaluation hierarchical model of system performance comprising a target layer, a criterion layer and an index layer; obtaining at least one subjective index weight vector through a subjective weighting method, and obtaining at least one objective index weight vector through an objective weighting method; performing comprehensive integration weighting on the subjective index weight vector and the objective index weight vector by adopting a genetic algorithm, and obtaining a comprehensive integration weighting vector; and improving the TOPSIS model in combination with the comprehensive integrated weighting vector, and comprehensively evaluating the system performance by using the improved TOPSIS model to obtain evaluation information. According to the method, the problem that the comprehensiveness, accuracy and objectivity of a method for comprehensively evaluating the system performance in the prior art need tobe improved is solved, and the method has good comprehensiveness, high accuracy and certain applicability.

The invention discloses a rail transit key node and a key road section identification method. The method includes: based on a complex network theory and a PageRank algorithm, calculating a topologicalindex value of the rail network as a node importance evaluation system value; carrying out evaluation value calculation on a node importance evaluation matrix by adopting three evaluation methods ofa grey correlation analysis method, a TOPSIS method and a principal component analysis method, determining weights of evaluation results by utilizing an entropy weight method, and finally obtaining importance values of the nodes and the road sections so as to identify the key nodes and the key road sections. According to the invention, identification of the key nodes of the rail transit network isobjectively and comprehensively considered; the key node importance degree calculation method is designed by using relevant theories such as a complex network and comprehensive evaluation, stations needing important maintenance in rail transit operation can be judged, the importance degrees of all the stations are ranked, and a choice is further provided for robustness analysis of the key nodes of the rail transit network.

The invention discloses an emergency plan evaluation method based on an improved TOPSIS method, which relates to the technical field of emergency plan evaluation and analysis. This method takes the emergency plan of water pollution accident as the research object and takes the emergency plan of water pollution accident as the research object, Based on the benefit index and cost index, the evaluation system is established, and the optimal emergency plan for water pollution emergencies is determined by the improved TOPSIS method.In the determination of index weights, the combination of AHP method and entropy method can get more reasonable and accurate index weights. Therefore, the evaluation method provided by the invention can provide better guidance for determining a more reasonable, scientific and effective optimal emergency plan. It solves the problem that the existing emergency plan research is mainly to study the preparation of the plan and recommendations, but can not determine the optimal plan, and provides technical support for better response to sudden environmental pollution events.

The invention provides an operation shop bottleneck recognition method based on a cluster analysis concept and a multiple attribute decision making theory. The method comprises the following steps of 1, utilizing dispatching optimization scheme as input of bottleneck recognition, determining feature attributes of a bottleneck recognition device and calculating the feature attribute values of the device according to the dispatching optimization result; 2, acquiring clustering clusters of the device under different distances and a parent-child relationship dendritic structure chart thereof on the basis of the similarity of a characteristic attribute excavating machine of the device by utilizing a hierarchical clustering method; 3, determining cluster centers of two sub-clusters of a final clustering cluster, comparing the attribute values of the cluster centers on the basis of a TOPSIS method and determining bottleneck clusters containing few device members; and 4, sequentially comparing sub-clusters of the bottleneck clusters and gradually obtaining main bottleneck clusters of different orders. According to the embodiment of the invention, the method provided by the invention can be used for solving the multi-bottleneck recognition problem which cannot be solved by the existing method.

The invention relates to an energy efficiency comprehensive evaluation method for a thermal power plant. The method comprises the following steps: building an energy efficiency comprehensive evaluation index system of the thermal power plant; determining comprehensive weight of the energy efficiency comprehensive evaluation indexes of the thermal power plant by using an order relation method and a sequence comprehensive method; analyzing by using a grey relational degree and building positive and negative ideal grey correlation decision matrixes; calculating weighting grey correlation decision matrixes through the combination of comprehensive index weight of the energy efficiency indexes; finally, calculating projection coefficient values of a unit to be evaluated according to a protection vector principle. By using a combination weighting method, the defect of single weighting is overcome; by combining TOPSIS, the grey relation theory and a projection vector theory, the weakness of grey correlation one-way evaluation is effectively avoided; meanwhile, a vector space of an index factor set is fully utilized, so that the method is particularly suitable for solving the energy efficiency evaluation problems of large-scale thermal power plants with more index factors and provides a new way for energy efficiency evaluation of the power plants.

The invention relates to a reliability evaluation method of an active power distribution network with a distributed power supply based on a TOPSIS method. The reliability evaluation method comprises astep of giving an initial network structure, a step of carrying out Monte-Carlo simulation hourly and analyzing a network according to a network structure obtained by the Monte-Carlo simulation, a step of judging the number of network cracking, carrying out flow calculation on the network according to the type of a cracked network and then adjusting according to a flow imbalance adjustment strategy, a step of counting and calculating reliability indexes according to the result of the flow calculation, a step of obtaining a specification decision matrix by using a vector normalization method,a step of constructing matrix A of results of the pairwise comparison of the reliability indexes, a step of checking the consistency of the matrix A, a step of obtaining an eigenvector W correspondingto a largest eigenvalue lambda max of the matrix A, wherein W=[omega1, omega2 ... to omega7]T, a step of constructing a weighted normative matrix X={xij}, wherein xij=omegaj*zij, i=1 to m, j=1 to 7,a step of calculating an ideal solution x[j]<*> and a negative ideal solution x[j] <0>, a step of calculating Euclidean distances of each scheme to the ideal solution and the negative ideal solution,and a step of calculating the comprehensive evaluation value of each scheme according to the formula C[i]<*>=d[i]<0> / (d[i]<0>+d[i]<*>), i=1 to m, and setting a quality sequence of the schemes according to the sequence of C[i]<*> from large to small.

The invention discloses an AGC power multi-objective random optimization distribution method based on improved TOPSIS-Q. The method comprises the steps that (1), a state discrete set and a motion discrete set are determined; (2), state-motion value functions and state-motion probability matrixes are initialized; (3), real-time output active power of sets of a current control period regional power grid is collected; (4), immediate award values of optimization objectives are obtained; (5), the state-motion value functions of the optimization objectives are undated; (6), normalization processing is carried out on state-motion value matrixes through a range transformation method to solve optimal weight coefficients; (7), greed motion under the current state is solved, and the state-motion probability matrixes are updated; (8), motion is selected according to the current state-motion probability matrixes, and the step (3) is executed again when the next control period comes. The multi-objective optimization method is combined with an improved TOPSISI multi-objective decision method, and the dynamic multi-objective random optimization requirement for an AGC closed-loop control system with the high requirement for real-time performance can be met.

The invention discloses a voltage sag level comprehensive evaluation method comprises based on an IEEE Std 1564-2014 standard, selecting amplitude, frequency, energy and severity indexes to constructa node index vector; trending and nondimensionalizing the original index data by using a reverse inverse transformation method and an averaging method so as to preprocess the indexes; constructing a determining matrix based on an analytic hierarchy process, and subjectively weighting the indexes; objectively evaluating the indexes by using a principal component analysis method based on a TOPSIS model; and comprehensively evaluating the node sag level by using combination weighting. The method solves the excessive information redundancy level between sag indexes, combines the advantages of subjective experience and objective information by the combination weighting method, and overcomes the defect that a traditional voltage sag evaluation method just uses a single weighting method and cannot fully describe the defects of the sag feature. A provided test method can describe the performance in all aspects of the comprehensive evaluation method accurately and comprehensively.

This paper discloses an active distribution network optimal dispatching method which takes into account the interests of different agents, includes the following steps: considering schedulable distributed generation, Energy storage, on-load tap changer, active control and management of packet switching capacitors and demand side resources, While considering environmental benefits, Taking into account the interests of distribution companies and distributed generation companies, an active distribution network day-ahead optimal dispatching model is established to minimize the operating cost of distribution companies, maximize the net income of distributed generation companies and minimize the emission of pollutants, and an improved bat algorithm based on diversity strategy is proposed to solve the problem. The entropy-weighted TOPSIS method is used to make comprehensive decision, and the optimal scheduling scheme is selected from the Pareto solution set.

The invention relates to a full life cycle-based numerical control machine tool sustainability evaluation method. Firstly, life cycle stages of a numerical control machine tool are divided into a design stage, a manufacturing stage, an assembly stage, a transportation stage, a use stage, a recovery stage and a waste treatment stag; then influence factors of environmental, economic and social factors of each life cycle stage are identified; qualitative analysis and quantitative analysis are performed on the factors; a comprehensive evaluation method based on TOPSIS is established; product sustainability evaluation indexes and a quantitative method thereof are provided; a quantitative mathematical model is built; quantitative indexes are quantified in a grade division mode; a numerical control machine tool sustainability index SI of a numerical control machine tool sustainability evaluation process is adopted as a comparison standard of a to-be-evaluated object; a relative comparison result is provided; and values of different dimensions and different time points or time periods are used for performing calculation and comparison.

The invention provides a method for predicting spontaneous combustion danger in gas extraction boreholes, and relates to the technical field of coal mine safety engineering. The invention provides themethod for predicting spontaneous combustion danger in the gas extraction boreholes in a coal mine. In order to find out a spontaneous combustion danger degree of the gas extraction boreholes and therelationship between spontaneous combustion of the boreholes and influencing factors thereof during gas extraction, the invention provides a G2 weighting method based on improved CRITIC. Through theintroduction of a Euclidean distance function and the establishment of an optimal decision-making model, the G2 weighting method is modified by virtue of a CRITIC weighting method so as to obtain a comprehensive weight of each index. Based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), namely a ''driving function'' principle of the TOPSIS theory, the G2 weighting method establishes a G2-TOPSIS borehole spontaneous combustion danger judgment model, and analyzes a closeness degree so as to finally predict the spontaneous combustion danger degree of the boreholes.

The invention discloses a capacity optimization method for a park-level integrated energy system based on investment constraints. The method comprises steps that S1, a load type required by a park isdetermined and recorded as a sold energy set, and various types of energy load demands are predicted; S2, a form of externally available energy is determined and recorded as a purchased energy form set; S3, corresponding energy production device and conversion device types are determined and recorded as a device type set; S4, relevant available energy storage devices are determined and listed intoan energy storage device set; S5, an alternative scheme combination set is formed according to a random initialization scheme; S6, a corresponding annualized device investment amount is calculated incombination with the alternative scheme combination set to form a reserved scheme set; S7, the reserved scheme set is screened by utilizing investment constraints to form a reserved scheme set; S8, the reserved scheme set is inputted into a multi-target collaborative optimization model; and S9, the TOPSIS method is utilized to solve an optimal configuration scheme.

The invention provides a smart energy system evaluation method and device based on an AHP-improved entropy weight method-TOPSIS. An evaluation index system is established on the basis of deep analysisof the intelligent energy system; the subjective weight of an index is determined by adopting an analytic hierarchy process, the objective weight of the index is determined by adopting an improved entropy weight method, the subjective weight and the objective weight are combined into a combined weight, and the smart energy system of each stage of each region is scored and sorted by adopting a TOPSIS method to obtain a comprehensive evaluation result. The subjectivity of expert experience and the objectivity of real data can be fused, and suggestions are provided for the next development of each intelligent energy system.

The invention relates to the field of machine tool property evaluation, and in particular to a comprehensive machine tool property evaluation method based on an entropy weight and a membership theory. On the basis that various property data of a machine tool are tested, the various property data of the machine tool are subjected to dimensionless standardization treatment by using a TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method; evaluation degrees of property indexes are established according to expert knowledge; a single factor evaluation set of the machine tool properties is determined by using the membership theory; the comprehensive weight is calculated based on the entropy weight and the expert experience; and finally, the comprehensive evaluation result of the machine tool properties is obtained through the single factor evaluation set and the comprehensive weight. The method is used for evaluating comprehensive properties of various machine tools and used for comparing the comprehensive properties of various similar machine tools, a scientific and operable evaluation method and procedures are provided for the comprehensive machine tool property evaluation, and the problem that the machine tool properties cannot be quantitatively evaluated is solved.

The invention provides an operation workshop bottleneck identification method taking a machine attribute as an internal number. Firstly, obtaining a scheduling optimizing scheme for a scheduling problem by an optimizing method; and secondly, building a multi-attribute bottleneck identification model of an interval attribute value, converting a bottleneck identification problem into a multi-attribute decision problem by comprehensively evaluating a candidate machine according to multiple evaluation attributes, and then making a final bottleneck decision by using an improved three-parameter interval TOPSIS. According to the invention, the improved three-parameter interval TOPSIS bottleneck identification method is used to strengthen the information expression capability of the interval, and improve the information accuracy of the interval; the weight determination problem of difference in distribution probability of the attribute interval is solved due to an improved three-parameter deviation formula, and the weight of the machine attribute can be effectively determined; and the approach degree Ci of the multi-attribute interval bottleneck identification method fully digs the information contained in the equipment attribute, and has higher bottleneck identification quality compared with a determinacy multi-attribute bottleneck identification method.

The invention provides a multi-objective optimization method for current limiting strength of a horizontal well inflow control device (ICD). The multi-objective optimization method includes building ahorizontal well ICD completion flow coupling model; taking the horizontal well yield and water breakthrough time variable coefficient as the objective function, setting constraint conditions and building an ICD current limiting strength multi-objective optimization model; solving the multi-objective optimization model through an NSGA-II algorithm to obtain the optimal solution set of the multi-objective optimization method; ranking according to the the distance from all solutions in the optimal solution set to the ideal optimal solution and the ideal inferior solution through the Topsis method, thereby acquiring the optimal solution of the current limiting strength of the horizontal well ICD .

The invention discloses a site selection method for post-earthquake medical emergency facilities. The method comprises steps that (1), candidate points for the post-earthquake medical emergency facilities are determined; (2), influencing factors for site selection optimization of the post-earthquake medical emergency facilities are analyzed according to the specific conditions of a region; (3), weights of the various influencing factors are calculated through utilizing TOPSIS; (4), fairness, high efficiency, the maximum coverage range and appropriate cost consideration are taken as targets toestablish a base-level emergency medical facility site selection model; (5), a post-earthquake advanced emergency medical command post site selection model is established based on the base-level emergency medical facility site selection model of the step (4); and (6), the model is solved by the nested genetic algorithm, and a base-level medical emergency facility point set and advanced emergency medical command posts are determined. The site selection method is advantaged in that the site selection method can quickly and scientifically determine the medical emergency facility points, and the method is of great significance to reduce casualties after earthquakes.

The invention discloses an evaluation method for an equipment manufacture supplier. The method comprises the following steps that: on the basis of an order relation analysis method, an entropy method,a TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method and a grey correlation degree analysis method, carrying out supplier evaluation, perfecting a supplier evaluation management system on the basis of historical data and a model algorithm, and improving a supplier management refinement level; calculating index weight; adopting an order relation analysis method to carrying out sorting on indexes, adopting the entropy method to correct the index weight, and determining the index weight; adopting a supplier evaluation method algorithm; according to the above calculation result, utilizing the TOPSIS method and the grey correlation degree analysis method as basic algorithms, and approaching to the practical real ability level of the supplier; and forming one setof complex equipment manufacture supplier evaluation calculation model. By use of the method, the supplier evaluation management system is perfected, the supplier management refinement level is improved, and the problem that objectivity and fairness are lost since the supplier evaluation is based on manual evaluation is avoided.