| AGGREGATION OF FUZZY OPINIONS UNDER GROUP DECISION-MAKING BASED ON SIMILARITY AND DISTANCE |
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| 引用本文： | Chengguo LU Jibin LAN Zhongxing WANG. AGGREGATION OF FUZZY OPINIONS UNDER GROUP DECISION-MAKING BASED ON SIMILARITY AND DISTANCE[J]. 系统科学与复杂性, 2006, 19(1): 63-71. DOI: 10.1007/s11424-006-0063-y |
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| 作者姓名： | Chengguo LU Jibin LAN Zhongxing WANG |
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| 作者单位： | [1]School of Mathematics and Information Science, Guangxi University, Nanning 530004, China [2]School of Economics and Management, South West Jiao-tong University, Chengdu 610031, China |
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| 摘 要： | In this article,a new method for aggregating fuzzy individual opinions into a group consensusopinion is proposed.To obtain the aggregation weights of each individual opinion,a consistency indexof each expert with the other experts is introduced based on similarity and distance.The importance ofeach expert is also taken into consideration in the process of aggregation.Finally.a numerical exampleis presented to illustrate the efficiency of the procedure.
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| 关 键 词： | 一致度 模糊个体评价 模糊数 集体舆论评价 集体决定制造 相似性 |
| 收稿时间： | 2004-12-06 |
| 修稿时间： | 2004-12-062005-09-07 |
Aggregation of Fuzzy Opinions Under Group Decision-Making Based on Similarity and Distance |
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| Chengguo Lu,Jibin Lan,Zhongxing Wang. Aggregation of Fuzzy Opinions Under Group Decision-Making Based on Similarity and Distance[J]. Journal of Systems Science and Complexity, 2006, 19(1): 63-71. DOI: 10.1007/s11424-006-0063-y |
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| Authors: | Chengguo Lu Jibin Lan Zhongxing Wang |
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| Affiliation: | (1) School of Mathematics and Information Science, Guangxi University, Nanning, 530004, China;(2) School of Economics and Management, South West Jiao-tong University, Chengdu, 610031, China |
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| Abstract: | In this article, a new method for aggregating fuzzy individual opinions into a group consensus opinion is proposed. To obtain the aggregation weights of each individual opinion, a consistency index of each expert with the other experts is introduced based on similarity and distance. The importance of each expert is also taken into consideration in the process of aggregation. Finally, a numerical example is presented to illustrate the efficiency of the procedure. |
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| Keywords: | Consistency degree fuzzy individual opinions fuzzy numbers group consensus opinion group decision-making. |
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