CN113159624A - Cloud 3D printing service evaluation multi-attribute decision method based on intuitionistic fuzzy number - Google Patents

Cloud 3D printing service evaluation multi-attribute decision method based on intuitionistic fuzzy number Download PDF

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CN113159624A
CN113159624A CN202110517479.6A CN202110517479A CN113159624A CN 113159624 A CN113159624 A CN 113159624A CN 202110517479 A CN202110517479 A CN 202110517479A CN 113159624 A CN113159624 A CN 113159624A
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evaluation
cloud
printing
indexes
index
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张成雷
张远明
王晓杰
高艳红
孙成通
庄申乐
亓琳
庄娇娇
王振乾
刘佳佳
侯宗香
齐玉瑞
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Linyi University
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06395—Quality analysis or management

Abstract

The invention discloses a cloud 3D printing service evaluation multi-attribute decision method based on an intuitive fuzzy number, belongs to the field of cloud 3D printing, and is used for evaluation and quantification. In view of the technical scheme, the cloud 3D printing service evaluation index fuzzification processing method and device can fuzzify data in the cloud 3D printing service evaluation index to obtain a more accurate evaluation result.

Description

Cloud 3D printing service evaluation multi-attribute decision method based on intuitionistic fuzzy number
Technical Field
The invention belongs to the field of cloud 3D printing, and particularly relates to a cloud 3D printing service evaluation multi-attribute decision method based on intuitive fuzzy numbers.
Background
After the cloud 3D printing service is completed, the platform providing the cloud 3D printing service may send a service quality evaluation for the provided cloud 3D printing service to the user, and because in the process of feature selection and extraction of a service quality evaluation index, some features are not easily specifically quantified, and cannot be described with an accurate language and number, some ambiguous words need to be used for evaluation, for example: "good", "bad", "extremely bad", and the like. How to fuzzify some indexes which cannot be specifically quantized becomes a technical problem to be solved by the industry.
Disclosure of Invention
The invention aims to provide a cloud 3D printing service evaluation multi-attribute decision method based on an intuitionistic fuzzy number, which can fuzzify data in a cloud 3D printing service evaluation index to obtain a more accurate evaluation result.
In order to achieve the purpose, the invention is realized by the following technical scheme:
a cloud 3D printing service evaluation multi-attribute decision method based on intuitive fuzzy numbers comprises the following steps,
acquiring a continuous data index and a discrete data index in a cloud 3D printing evaluation index;
step two, if the user evaluates the continuous data indexes in the cloud 3D printing evaluation indexes, the expected value interval of one party providing the cloud 3D printing service in the continuous data indexes to the evaluation indexes is
Figure BDA0003062212960000011
After the service resource configuration in the cloud 3D printing order task execution manufacturing process is completed, the obtained evaluation index q of the user on the service resourcej，qjIs a specific value; after a buyer purchases a printed product, the fuzzy service evaluation of the manufacturing task by the client is obtained to carry out quantitative processing.
Step three, normalization processing is carried out on each service evaluation result obtained in the step two, and the quantification processing of continuous data indexes is carried out by adopting the following formula
Figure BDA0003062212960000012
Wherein the content of the first and second substances,
Figure BDA0003062212960000021
is the minimum value of each evaluation index,
Figure BDA0003062212960000022
is the maximum value of each evaluation index;
step four, acquiring corresponding intuitive fuzzy number evaluation P from the following table according to the calculation resultFCorresponding fuzzy grade k and membership degree range P for analyzing and evaluating ecological quality of productk
Figure BDA0003062212960000023
Further, in the second step of the present invention, if the user evaluates the discrete data index in the cloud 3D printing evaluation index, the expected value interval of the evaluation index for the party providing the cloud 3D printing service in the discrete evaluation index is [ Vmin,Vmax]After the service resource configuration in the cloud 3D printing order task execution manufacturing process is completed, the obtained user evaluation index is V, and if V is a specific value, the user evaluation index is passed
Figure BDA0003062212960000024
Calculating and obtaining membership degree, and obtaining corresponding intuition fuzzy number evaluation V through tableFCorresponding fuzzy grade k and evaluation value V for analyzing and evaluating ecological quality of productk。
Further, the cloud 3D printing evaluation index in the invention includes time T, cost C, quality Q, response R, reliability Rel, fault tolerance Ft, matching degree Mat, flexible Flex, security SF, and comprehensive satisfaction Sa, where time T, cost C, matching degree Mat belong to discrete data indexes, and quality Q, response R, reliability Rel, fault tolerance Ft, flexible Flex, security SF, and comprehensive satisfaction Sa are continuous data indexes.
Further, the intuitive blur number evaluation P described in the present inventionFIs calculated by the formula
Figure BDA0003062212960000025
Figure BDA0003062212960000026
Wherein FkIs a factor index set X ═ X formed by cloud 3D printing evaluation indexes1,x2,…,xmWeight value of element value of line k in }, UksIs a factor index set X ═ X formed by cloud 3D printing evaluation indexes1,x2,…,xmAnd (4) obtaining a ratio judgment scale value by comparing the element value of the kth row and the s column with other element values.
Further, the intuitive fuzzy number evaluation described in the present invention
Figure BDA0003062212960000027
Further, the intuitive fuzzy number evaluation described in the present invention
Figure BDA0003062212960000028
Compared with the prior art, the invention has the beneficial effects that:
the invention can utilize the uncertainty factors existing in certain characteristic evaluation performance index characteristics to carry out the operation calculation of the weighting operator by utilizing the fuzzy numbers of the respective sub-characteristics to obtain the optimal index set and the membership degree, thereby carrying out fuzzification processing on each evaluation index and finally obtaining the evaluation result.
Detailed Description
The technical solution of the present invention will be further described and illustrated with reference to the following examples.
The core index of cloud 3D printing service evaluation refers to a cloud 3D printing service evaluation index of a ten-dimensional target component in a cloud 3D printing service quality evaluation index and a platform comprehensive performance evaluation index, and mainly comprises three important indexes of a seven-major index in a cloud 3D printing QoS evaluation index and a platform comprehensive performance evaluation index. The cloud 3D printing QoS and comprehensive performance evaluation indexes comprise time T, cost C, quality Q, response R, reliability Rel, fault tolerance Ft, matching degree Mat, flexible Flex, safety SF and comprehensive satisfaction Sa. The characteristics of the ten evaluation performance indexes and the main environmental influence types thereof can be used for gray fuzzy comprehensive evaluation and calculation of the evaluation performance indexes, wherein time T, cost C and matching degree Mat belong to discrete indexes, quality Q, response R, reliability Rel, fault tolerance Ft, flexible Flex, safety SF and comprehensive satisfaction Sa belong to continuous data indexes, and the two types of data indexes are respectively processed according to a gray fuzzy comprehensive evaluation method.
Before processing the data index, 9-level linguistic variable intuitive fuzzy values need to be defined, as shown in the following table.
Figure BDA0003062212960000031
When continuous data indexes such as quality Q, response R, reliability Rel, fault tolerance Ft, flexible Flex, safety SF and comprehensive satisfaction Sa are evaluated.
Weight distribution calculation based on analytic hierarchy process
Factor index set X ═ X1,x2,…,xmComparing the kth element value with other element values, and judging the scale value U of the kth element value as:
U＝{Uk1,Uk2,…,Ukm}
therefore, the weight assignment based on the analytic hierarchy process calculates F:
Figure BDA0003062212960000041
s＝1，2，3，…，m。
wherein, FkIs the weight value of the k-th line element value, UksIs the ratio judgment scale value of the kth row and the s column. Therefore, the hierarchal analysis based weight distribution is calculated as:
Figure BDA0003062212960000042
s＝1，2，3，…，m。
in summary, the gray fuzzy comprehensive evaluation P is utilizedFShould be calculated as
Figure BDA0003062212960000043
Suppose a certain continuity type data index PFHas a value range of [ Pmin,100％]. In the cloud 3D printing order task execution manufacturing process, the service quality evaluation index is dynamic, so that when the continuous data evaluation index P is fuzzified, the intuitive fuzzy number evaluation PFCan be marked as
Figure BDA0003062212960000044
Wherein, PkThe evaluation value is used for analyzing and evaluating the ecological quality of the product.
For example, a manufacturing task evaluation meansThe expected value interval of the index continuous data index is [ 20%, 100%]After the service resource configuration in the cloud 3D printing order task execution manufacturing process is completed, the obtained P iskThe specific value is about 70%, and 70% is in the expected value range [ 20%, 100%]In the method, after a purchaser purchases a printed product, a manufacturing task is subjected to service evaluation, and a service evaluation result is given, wherein the 3D printing effect is good, the resin is slightly brittle, parts are damaged, and the whole is still possible, the precision is high, and the surface is smooth.
According to the service evaluation results, normalization calculation processing is carried out on each service evaluation result, and the normalization calculation processing is carried out by adopting the following formula so as to obtain the corresponding membership value:
Figure BDA0003062212960000045
calculated membership of
Figure BDA0003062212960000046
The calculated value 0.625 is assigned to 0.55, 0.65 according to the value interval shown in the defined 9-level linguistic variable intuitive fuzzy value]Interval, i.e. the obtained intuitive fuzzy number evaluation PFAre (0.50, 0.40, 0.10), the linguistic variables are medium, and the blur level is 5. I.e. k is 5, degree of membership P5In the range of [0.55, 0.65 ]]。
For the discrete index, if the expected value interval of a certain task evaluation index V is [20,50], after a cloud 3D printing buyer purchases a printed product, service evaluation is performed on a manufacturing task, and the evaluation result is given as follows:
quality of service: the effect is good, 8 points;
the delivery speed is as follows: the printing speed is finished in three days, and 6 minutes is spent;
express packaging: the packaging adopts a carton, and the additional foam plays a protective role and is divided into 8 minutes;
the service of the distributor: the express delivery personnel deliver the express to a collection shop for 7 points;
after-sale service: no problem occurred for the moment, 5 points.
That is, after the service volunteer configuration in the order task execution manufacturing process is completed, the specific value of the evaluation index thereof is about 34 points.
According to the service evaluation results, normalization calculation processing is carried out on each service evaluation result, and a specific quantification formula of the discrete data index is as follows:
Figure BDA0003062212960000051
wherein
Figure BDA0003062212960000052
From the above table, it can be seen that the value of 0.467 in the membership calculation result belongs to V4＝[0.40,0.55]If the corresponding blur level is 4, the corresponding intuitive blur number evaluation value V isFIs (0.40,0.65, 0.15).
The quantized data of the evaluation indexes of different types can be used as a data source of a Hybrid multi-objective particle swarm optimization (BM-MOPSO) based on the Baldwin effect to perform Model solution, on one hand, the effectiveness of the Hybrid multi-objective particle swarm optimization for solving the service evaluation problem is verified, and on the other hand, the problems that the current Hybrid multi-objective particle swarm optimization is easy to fall into local optimization and has low convergence precision exist.
Finally, although the present description refers to embodiments, not every embodiment contains only a single technical solution, and such description of the present description is for clarity reasons only, and those skilled in the art should make the description as a whole, and the technical solutions in the embodiments can be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims (6)

1. A cloud 3D printing service evaluation multi-attribute decision method based on intuitionistic fuzzy numbers is characterized by comprising the following steps: comprises the following steps of (a) carrying out,
acquiring a continuous data index and a discrete data index in a cloud 3D printing evaluation index;
step two, if the user evaluates the continuous data indexes in the cloud 3D printing evaluation indexes, the expected value interval of one party providing the cloud 3D printing service in the continuous data indexes to the evaluation indexes is
Figure FDA0003062212950000011
After the service resource configuration in the cloud 3D printing order task execution manufacturing process is completed, the obtained evaluation index q of the user on the service resourcej，qjIs a specific value; after the purchaser purchases the printed product, the customer's assessment of the fuzziness of the manufacturing job is obtained.
Step three, normalization processing is carried out on each service evaluation result obtained in the step two, and the quantification processing of continuous data indexes is carried out by adopting the following formula
Figure FDA0003062212950000012
Wherein the content of the first and second substances,
Figure FDA0003062212950000013
is the minimum value of each evaluation index,
Figure FDA0003062212950000014
is the maximum value of each evaluation index;
step four, acquiring corresponding intuitive fuzzy number evaluation P from the following table according to the calculation resultFCorresponding fuzzy grade k and membership degree range P for analyzing and evaluating ecological quality of productk
Figure FDA0003062212950000015
2. The cloud 3D printing service evaluation multi-attribute decision method based on intuitive fuzzy numbers according to claim 1, characterized in that: in the second step, if the user evaluates the discrete data indexes in the cloud 3D printing evaluation indexes, the expected value interval of the party providing the cloud 3D printing service in the discrete evaluation indexes to the evaluation indexes is [ V ]min,Vmax]After the service resource configuration in the cloud 3D printing order task execution manufacturing process is completed, the obtained user evaluation index is V, and if V is a specific value, the user evaluation index is passed
Figure FDA0003062212950000016
Calculating and obtaining membership degree, and obtaining corresponding intuition fuzzy number evaluation V through tableFCorresponding fuzzy grade k and evaluation value V for analyzing and evaluating ecological quality of productk。
3. The cloud 3D printing service evaluation multi-attribute decision method based on intuitive fuzzy numbers according to claim 2, characterized in that: the cloud 3D printing evaluation indexes comprise time T, cost C, quality Q, response R, reliability Rel, fault tolerance Ft, matching degree Mat, flexible Flex, safety SF and comprehensive satisfaction Sa, wherein the time T, the cost C and the matching degree Mat belong to discrete data indexes, and the quality Q, the response R, the reliability Rel, the fault tolerance Ft, the flexible Flex, the safety SF and the comprehensive satisfaction Sa are continuous data indexes.
4. The cloud 3D printing service evaluation multi-attribute decision method based on intuitive fuzzy numbers according to claim 3, characterized in that: the intuitive blur number evaluation PFIs calculated by the formula
Figure FDA0003062212950000021
Figure FDA0003062212950000022
Wherein FkIs a factor index set X ═ X formed by cloud 3D printing evaluation indexes1,x2,…,xmWeight value of element value of line k in }, UksIs a factor index set X ═ X formed by cloud 3D printing evaluation indexes1,x2,…,xmAnd (4) obtaining a ratio judgment scale value by comparing the element value of the kth row and the s column with other element values.
5. The cloud 3D printing service evaluation multi-attribute decision method based on intuitive fuzzy numbers according to claim 4, characterized in that: the intuitive fuzzy number evaluation
Figure FDA0003062212950000023
6. The cloud 3D printing service evaluation multi-attribute decision method based on intuitive fuzzy numbers according to claim 5, characterized in that: the intuitive fuzzy number evaluation
Figure FDA0003062212950000024
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