

FOLLOWUS
College of Information System and Management, National University of Defense Technology, Changsha 410073, China
E-mail: zxxandxx@163.com
Received:24 June 2015,
Accepted:25 September 2015,
Published:2016-03
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Xiao-xiong ZHANG, Bing-feng GE, Yue-jin TAN. A consensus model for group decision making under interval type-2 fuzzy environment[J]. Frontiers of Information Technology & Electronic Engineering, 2016, 17(3): 237-249.
Xiao-xiong ZHANG, Bing-feng GE, Yue-jin TAN. A consensus model for group decision making under interval type-2 fuzzy environment[J]. Frontiers of Information Technology & Electronic Engineering, 2016, 17(3): 237-249. DOI: 10.1631/FITEE.1500198.
目的
2
针对区间2型模糊数环境下的群决策问题,提出一种新的共识模型,同时针对决策者权重不一致情形,提出一种新的反馈机制。
创新点
2
提出了一种用于处理区间2型模糊数环境下的群决策问题的共识模型,充分发挥了2型模糊数表示信息的灵活性和广泛性。同时,在整个决策过程中考虑专家权重的影响,根据专家不同权重制定不同的反馈意见。
方法
2
首先,专家结合自身经验知识,利用区间2型模糊数对问题进行评价赋值。然后,通过计算不同的一致性指标来检测当前专家们的意见是否趋于一致。若是,则转入方案选型阶段;若不是,则转入反馈机制。反馈机制主要是对不同的专家给予一定的修改意见,以指导专家对自身偏好进行调整,提高整体意见的一致性。总的来说,专家自身权值越大,则其需要调整修改的偏好值越少;反之,专家自身权值越小,则其需要调整修改的偏好值越多(图2)。
结论
2
针对群决策问题,提出了用于处理2型区间模糊数环境下的共识模型,计算高效,结论可信。
We propose a new consensus model for group decision making (GDM) problems
using an interval type-2 fuzzy environment. In our model
experts are asked to express their preferences using linguistic terms characterized by interval type-2 fuzzy sets (IT2 FSs)
because these can provide decision makers with greater freedom to express the vagueness in real-life situations. Consensus and proximity measures based on the arithmetic operations of IT2 FSs are used simultaneously to guide the decision-making process. The majority of previous studies have taken into account only the importance of the experts in the aggregation process
which may give unreasonable results. Thus
we propose a new feedback mechanism that generates different advice strategies for experts according to their levels of importance. In general
experts with a lower level of importance require a larger number of suggestions to change their initial preferences. Finally
we investigate a numerical example and execute comparable models and ours
to demonstrate the performance of our proposed model. The results indicate that the proposed model provides greater insight into the GDM process.
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