Fuzzy Evidential Reasoning Approach for LCMS Competitiveness Evaluation under Incomplete Information

Fuzzy Evidential Reasoning Approach for LCMS Competitiveness Evaluation under Incomplete Information

In order to evaluate scientifically low carbon manufacturing system (LCMS) competitiveness under incomplete information, this paper, using fuzzy mathematics theory and evidential reasoning approach, proposes an evaluation method. Firstly, through fuzzy evaluation the influence factors of LCMS compet...

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Main Authors: Bengang Gong, Xiaoqi Zhang, Dandan Guo, Yunmiao Gui
Format: Article
Language:English
Published: Hindawi Limited 2015-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2015/949232
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spelling doaj-c9d5657ae3cc40749ab266d86de1b9b62020-11-24T23:02:50ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472015-01-01201510.1155/2015/949232949232Fuzzy Evidential Reasoning Approach for LCMS Competitiveness Evaluation under Incomplete InformationBengang Gong0Xiaoqi Zhang1Dandan Guo2Yunmiao Gui3School of Management Engineering, Anhui Polytechnic University, Wuhu, Anhui 241000, ChinaSchool of Management Engineering, Anhui Polytechnic University, Wuhu, Anhui 241000, ChinaSchool of Management Engineering, Anhui Polytechnic University, Wuhu, Anhui 241000, ChinaSchool of Management Engineering, Anhui Polytechnic University, Wuhu, Anhui 241000, ChinaIn order to evaluate scientifically low carbon manufacturing system (LCMS) competitiveness under incomplete information, this paper, using fuzzy mathematics theory and evidential reasoning approach, proposes an evaluation method. Firstly, through fuzzy evaluation the influence factors of LCMS competitiveness are characterized by a set of evaluation grades. Secondly, the analytical evidential theory algorithms are used to aggregate the evaluation grades of multiple influence factors, and the assessed values of LCMS competitiveness are obtained under each evaluation index and the system overall goal. According to the evaluation value, the key influence factors of LCMS competitiveness, which need to be improved and enhanced, are found. Lastly, a numerical example is provided.http://dx.doi.org/10.1155/2015/949232
collection DOAJ
language English
format Article
sources DOAJ
author Bengang Gong
Xiaoqi Zhang
Dandan Guo
Yunmiao Gui
spellingShingle Bengang Gong
Xiaoqi Zhang
Dandan Guo
Yunmiao Gui
Fuzzy Evidential Reasoning Approach for LCMS Competitiveness Evaluation under Incomplete Information
Mathematical Problems in Engineering
author_facet Bengang Gong
Xiaoqi Zhang
Dandan Guo
Yunmiao Gui
author_sort Bengang Gong
title Fuzzy Evidential Reasoning Approach for LCMS Competitiveness Evaluation under Incomplete Information
title_short Fuzzy Evidential Reasoning Approach for LCMS Competitiveness Evaluation under Incomplete Information
title_full Fuzzy Evidential Reasoning Approach for LCMS Competitiveness Evaluation under Incomplete Information
title_fullStr Fuzzy Evidential Reasoning Approach for LCMS Competitiveness Evaluation under Incomplete Information
title_full_unstemmed Fuzzy Evidential Reasoning Approach for LCMS Competitiveness Evaluation under Incomplete Information
title_sort fuzzy evidential reasoning approach for lcms competitiveness evaluation under incomplete information
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2015-01-01
description In order to evaluate scientifically low carbon manufacturing system (LCMS) competitiveness under incomplete information, this paper, using fuzzy mathematics theory and evidential reasoning approach, proposes an evaluation method. Firstly, through fuzzy evaluation the influence factors of LCMS competitiveness are characterized by a set of evaluation grades. Secondly, the analytical evidential theory algorithms are used to aggregate the evaluation grades of multiple influence factors, and the assessed values of LCMS competitiveness are obtained under each evaluation index and the system overall goal. According to the evaluation value, the key influence factors of LCMS competitiveness, which need to be improved and enhanced, are found. Lastly, a numerical example is provided.
url http://dx.doi.org/10.1155/2015/949232
work_keys_str_mv AT benganggong fuzzyevidentialreasoningapproachforlcmscompetitivenessevaluationunderincompleteinformation
AT xiaoqizhang fuzzyevidentialreasoningapproachforlcmscompetitivenessevaluationunderincompleteinformation
AT dandanguo fuzzyevidentialreasoningapproachforlcmscompetitivenessevaluationunderincompleteinformation
AT yunmiaogui fuzzyevidentialreasoningapproachforlcmscompetitivenessevaluationunderincompleteinformation
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