scholarly journals A Reputation-Enhanced Hybrid Approach for Supplier Selection with Intuitionistic Fuzzy Evaluation Information

Mathematics ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 298 ◽  
Author(s):  
Zhijia Yan ◽  
Wenting Yang ◽  
Xiaoling Huang ◽  
Xiangrong Shi ◽  
Wenyu Zhang
Keyword(s):  
Supplier Selection ◽  
Comprehensive Evaluation ◽  
Hybrid Approach ◽  
Intuitionistic Fuzzy Set ◽  
Weighted Average ◽  
Fuzzy Evaluation ◽  
Entropy Weight ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Entropy ◽  
Entropy Weight Method

Selecting optimal suppliers in fuzzy environments has become a major challenge for enterprises. Reputation plays an important role in the process of supplier selection because of its fuzziness, dynamicity, and transitivity. In this study, we first present a novel intuitionistic fuzzy sets (IFS)-hyperlink-induced topic search (HITS) method that combines the intuitionistic fuzzy set with the hyperlink-induced topic search (HITS) algorithm to extend the ability of processing fuzzy information in order to obtain post-propagated reputation values of suppliers. Then, we employ the dynamic intuitionistic fuzzy weighted average operator to gain dynamic reputation values and other evaluation attribute values. After that, intuitionistic fuzzy entropy weight method is adopted to acquire more accurate weights for each evaluation attribute. Finally, we employ the Vlsekriterijumska Optimizacija I Kompromisno Resenje method to acquire comprehensive evaluation values of candidate supplier to select optimal suppliers. Two groups of experiments for supplier selection are given to explain feasibility and practicality of the proposed method.

Distribution Network Planning Based on Entropy Fuzzy Comprehensive Method

2010 ◽  
Vol 26-28 ◽  
pp. 780-784 ◽  
Author(s):  
Zheng Yuan Jia ◽  
Zhou Fan ◽  
Miao Miao Jiang
Keyword(s):  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Distribution Network ◽  
Network Planning ◽  
Fuzzy Comprehensive Evaluation ◽  
Fuzzy Evaluation ◽  
Entropy Weight ◽  
Planning Project ◽  
Entropy Weight Method ◽  
Distribution Network Planning

Comprehensive evaluation of distribute network planning is a multi-factors decision-making problem in complicated system. Combining with the factors of distribute network planning, established for the distribution network planning project evaluation fuzzy comprehensive evaluation model, and the entropy weight method is led into comprehensive fuzzy evaluation. It overcomes the shortages of traditional method, which requires to the independence of each index, and the weight coefficients of factors are automatically determined according to the opinion of experts. Finally, one example is used to verify the feasibility and practicality of the method.

scholarly journals Construction and Evaluation of the Integrated Perception Ecological Environment Indicator (IPEEI) Based on the DPSIR Framework for Smart Sustainable Cities

2020 ◽  
Vol 12 (17) ◽  
pp. 7112
Author(s):  
Yingbing Liu ◽  
Wenying Du ◽  
Nengcheng Chen ◽  
Xiaolei Wang
Keyword(s):  
Comprehensive Evaluation ◽  
Regional Scale ◽  
Environmental Indicators ◽  
Ecological Environment ◽  
Entropy Weight ◽  
Dpsir Framework ◽  
The Sustainable Development ◽  
Ecological Index ◽  
Entropy Weight Method ◽  
Environment Sustainability

Ecological environment evaluation is of great significance to achieve the Sustainable Development Goals (SDGs) and promote the harmonious development of economy, society, and environment. To evaluate environmental SDGs, single environmental indicators have been analyzed at national or large regional scale in some literature, while the urban integrated environment is ignored. Therefore, it is necessary to systematically and quantically evaluate the sustainability of ecological environment integrating the water, soil, and air environment at the urban scale. This study aims to construct the Integrated Perception Ecological Environment Indicator (IPEEI) based on the Driver-Pressure-State-Impact-Response (DPSIR) framework to solve the above-mentioned problems. The IPEEI model was proposed based on the three-level association mechanism of the Domain-Theme-Element, and the DPSIR framework conforming to the relevant standards for indicator determination. Moreover, the multi-dimensional, multi-thematic, and multi-urban quantitative evaluations were conducted using the entropy weight method, and the comprehensive evaluation grades by the Jenks natural breaks classification method of the geospatial analysis. Nine cities in the Wuhan Metropolitan Area were selected as the experimental areas. The results were consistent with the Ecological Index and local government’s planning and measures, which demonstrated that IPEEI can be effectively verified and applied for the evaluation of urban ecological environment sustainability.

scholarly journals Study on Development Sustainability of Atmospheric Environment in Northeast China by Rough Set and Entropy Weight Method

2019 ◽  
Vol 11 (14) ◽  
pp. 3793 ◽  
Author(s):  
Yuangang Li ◽  
Maohua Sun ◽  
Guanghui Yuan ◽  
Qi Zhou ◽  
Jinyue Liu
Keyword(s):  
Rough Set ◽  
Northeast China ◽  
Evaluation System ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Atmospheric Environment ◽  
Entropy Weight ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Environment Sustainability

In order to evaluate the atmospheric environment sustainability in the provinces of Northeast China, this paper has constructed a comprehensive evaluation model based on the rough set and entropy weight methods. This paper first constructs a Pressure-State-Response (PSR) model with a pressure layer, state layer and response layer, as well as an atmospheric environment evaluation system consisting of 17 indicators. Then, this paper obtains the weight of different indicators by using the rough set method and conducts equal-width discrete analysis and clustering analysis by using SPSS software. This paper has found that different discrete methods will end up with different reduction sets and multiple indicators sharing the same weight. Therefore, this paper has further introduced the entropy weight method based on the weight solution determined by rough sets and solved the attribute reduction sets of different layers by using the Rosetta software. Finally, this paper has further proved the rationality of this evaluation model for atmospheric environment sustainability by comparing the results with those of the entropy weight method alone and those of the rough set method alone. The results show that the sustainability level of the atmospheric environment in Northeast China provinces has first improved, and then worsened, with the atmospheric environment sustainability level reaching the highest level of 0.9275 in 2014, while dropping to the lowest level of 0.6027 in 2017. Therefore, future efforts should focus on reducing the pressure layer and expanding the response layer. Based on analysis of the above evaluation results, this paper has further offered recommendations and solutions for the improvement of atmospheric environment sustainability in the three provinces of Northeast China.

Coach Evaluation Method Based on AHP

2014 ◽  
Vol 551 ◽  
pp. 722-726
Author(s):  
Xin Cao
Keyword(s):  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Entropy Weight ◽  
Analytic Hierarchy ◽  
Time Line ◽  
The Hierarchical Structure ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Time Periods ◽  
Hierarchy Process

In order to evaluate coaches, this paper established the model of comprehensive evaluation based on analytic hierarchy process (AHP). Firstly, I establish the hierarchical structure of the system; Secondly, for researching the influence of time line horizon in analysis, I divided coaches into several groups by their career time and calculated the weights of indicators of each group using entropy weight method; Finally, calculate the weight between the criteria layer and objective layer. Female coach data is difficult to find, so I select 100 college basketball male coach data. Put the data into model and get a score. The score showed the final result which can give us a sort of reasonable coach list. This model can reduce the influence of different time periods for evaluation of the coach.

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