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Fuzzy TOPSIS evaluation method

An evaluation method and fuzzy technology, applied in data processing application, prediction, calculation and other directions, which can solve the problems of poor robustness of evaluation results, inability to choose closeness to customers, and not unique evaluation results, and achieve high consistency and robustness. awesome effect

Inactive Publication Date: 2017-04-26
CHONGQING UNIV
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Problems solved by technology

[0010] The existing TOPSIS evaluation method has been widely used, but its problem is: in the fuzzy environment, when the weight of the index changes, the calculation result using the Euler formula also changes, that is, the evaluation result is not unique, so the application The evaluation results obtained by the existing TOPSIS method are less robust
And the weight of the two indicators is: w 1 =0.8,w 2 =0.2, then the traditional Euler distance is used to calculate the closeness of the two candidate objects as R 1 =2 / (2+2)=0.5,R 2 =2 / (2+2)=0.5, it can be seen that the closeness of two candidate objects calculated using the traditional Euler distance formula is equal, and customers cannot choose according to the closeness

Method used

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Embodiment

[0080] In order to further illustrate the effectiveness and superiority of the present invention, the selection of an alliance partner is taken as an example below to prove it.

[0081] Case introduction: A fourth-party logistics company evaluates four candidate companies A, B, C, and D, and selects two of them to complete a logistics task.

[0082] Step 1: Obtain the original matrix of expert evaluation and the comprehensive weight of calculated indicators

[0083] The original decision matrix obtained through expert judgment is as follows:

[0084] Table 1 Expert judgment matrix for indicators

[0085]

[0086] In Table 1: C1-C13 represent 13 evaluation indicators, LI represents fuzzy number (1,1,3); MI represents fuzzy number (1,3,5); I represents fuzzy number (3,5,7); VI Represents fuzzy number (5,7,9); AI represents fuzzy number (7,9,9).

[0087] Table 2 Judgment matrix of experts on candidate partners

[0088]

[0089] In Table 2: VL stands for fuzzy numbers (1...

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Abstract

The invention discloses a fuzzy TOPSIS evaluation method, which comprises the following steps: 1) obtaining an expert evaluation original matrix and calculating index comprehensive weight; 2) calculating a weight standard decision matrix and positive and negative ideal solutions; and 3) calculating close degree of each candidate evaluation object. The improvement lies in that, in the step 3), a traditional Euler distance formula is improved, preferences of experts for evaluation indexes are considered, and a weight standard Euler distance function is constructed; and the close degree of each candidate evaluation object is calculated by utilizing weight standard Euler distance. The technical effects are that a ranking result obtained under a fuzzy condition has very high robustness; and meanwhile, the problem that when preferences of the experts for evaluation indexes are different, evaluation results are same in an existing TOPSIS evaluation method is prevented.

Description

technical field [0001] The invention belongs to a multi-attribute decision-making evaluation method, in particular to a fuzzy TOPSIS evaluation method. Background technique [0002] Multi-attribute decision-making evaluation is a scientific method used to solve multi-objective evaluation of limited schemes. Its purpose is to use mathematical methods to provide a scientific basis for the evaluation and ranking of programs. TOPSIS method, also known as multi-attribute decision-making approach to ideal solution, has been widely used in solving a large number of multi-attribute decision-making problems in society, economy and engineering. [0003] The basic steps of the TOPSIS method are: first, to obtain the original matrix evaluated by experts and the comprehensive weight of the calculation index; second, to calculate the weight standard decision matrix and positive and negative ideal solutions; put in order; [0004] In the third step, when calculating the closeness of the...

Claims

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Application Information

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IPC IPC(8): G06Q10/04
CPCG06Q10/04
Inventor 王旭何彦东林云周福礼
Owner CHONGQING UNIV
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