Partitioned Bonferroni mean based on linguistic 2-tuple for dealing with multi-attribute group decision making
Partitioned Bonferroni mean based on linguistic 2-tuple for dealing with multi-attribute group decision making
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DOI：
10.1016/j.asoc.2015.08.017
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发表时间：
2015-12-01
影响因子：
8.7
通讯作者：
Guha, Debashree
中科院分区：
文献类型：
--
作者：
Dutta, Bapi;Guha, Debashree
本文研究了一个多属性群体决策（MAGDM）问题，在这个问题中，决策者使用语言二元组来提供他们对备选方案的偏好。在决策过程中，引入了属性集特定结构的思想。假设属性被划分为若干类，分区内的成员相互关联，分区间的成员不存在相互关系。我们强调拥有一个聚合算子的重要性，以捕获属性之间表达的相互关系结构，我们将其称为分区邦费罗尼平均值（PBM）。我们还研究了所提出的PBM运营商的行为。为了进一步对给定的语言信息进行聚合，得到MAGDM中各备选方案的总体性能值，我们分析了语言二元组环境下的PBM算子，并开发了三种新的语言聚合算子：二元组语言PBM （2TLPBM）、加权二元组语言PBM （W2TLPBM）和语言加权二元组语言PBM （LW-2TLPBM）。基于最小化个体决策者意见与群体意见之间的总语言偏差的思想，我们开发了一种确定决策者权重的方法。最后，通过一个实例对所提方法进行了说明，并通过对比分析验证了所提方法的适用性。(C) 2015 Elsevier B.V.版权所有
In this study, a multi-attribute group decision making (MAGDM) problem is investigated, in which decision makers provide their preferences over alternatives by using linguistic 2-tuple. In the process of decision making, we introduce the idea of a specific structure in the attribute set. We assume that attributes are partitioned into several classes and members of intra-partition are interrelated while no interrelationship exists among inter partition. We emphasize the importance of having an aggregation operator, to capture the expressed inter-relationship structure among the attributes, which we will refer to as partition Bonferroni mean (PBM). We also investigate the behavior of the proposed PBM operator. Further to aggregate the given linguistic information to get overall performance value of each alternative in MAGDM, we analyze PBM operator in linguistic 2-tuple environment and develop three new linguistic aggregation operators: 2-tuple linguistic PBM (2TLPBM), weighted 2-tuple linguistic PBM (W2TLPBM) and linguistic weighted 2-tuple linguistic PBM (LW-2TLPBM). Based on the idea that total linguistic deviation between individual decision maker's opinions and group opinion should be minimized, we develop an approach to determine weight of the decision makers. Finally, a practical example is presented to illustrate the proposed method and comparison analysis demonstrates applicability of the proposed method. (C) 2015 Elsevier B.V. All rights reserved.