Models for Multiple Attribute Decision Making with Intuitionistic Fuzzy Information
Models for Multiple Attribute Decision Making with Intuitionistic Fuzzy Information
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DOI：
10.1142/s0218488507004686
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发表时间：
2007-06
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影响因子：
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通讯作者：
Z. Xu
中科院分区：
文献类型：
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作者：
Z. Xu
直觉模糊集是由Atanassov [K. Atanassov，“Intuitionistic fuzzy sets”，Fuzzy Sets and Systems 20（1986）87-96]作为Zadeh模糊集[L. A. Zadeh，“Fuzzy Sets”，Information and Control 8（1965）338-353]来处理模糊性和不确定性。研究了属性权重信息不完全且属性值用直觉模糊数表示的多属性决策问题。首先定义了直觉模糊理想解的概念，然后基于直觉模糊理想解和距离测度建立了属性权重的优化模型。此外，基于所开发的模型，我们开发了一些程序的排序方案在不同的情况下，并扩展所开发的模型和程序来处理区间值直觉模糊信息的多属性决策问题。最后，我们给出了一些说明性的例子来验证所开发的模型和程序的有效性和实用性。
The intuitionistic fuzzy set (IFS) characterized by a membership function and a non-membership function, was introduced by Atanassov [K. Atanassov, "Intuitionistic fuzzy sets", Fuzzy Sets and Systems 20 (1986) 87–96] as a generalization of Zadeh' fuzzy set [L. A. Zadeh, "Fuzzy Sets", Information and Control 8 (1965) 338–353] to deal with fuzziness and uncertainty. In this paper, we investigate the multiple attribute decision making (MADM) problems, in which the information about attribute weights is incomplete, and the attribute values are expressed in intuitionistic fuzzy numbers (IFNs). We first define the concept of intuitionistic fuzzy ideal solution (IFIS), and then, based on the IFIS and the distance measure, we establish some optimization models to derive the attribute weights. Furthermore, based on the developed models, we develop some procedures for the rankings of alternatives under different situations, and extend the developed models and procedures to handle the MADM problems with interval-valued intuitionistic fuzzy information. Finally, we give some illustrative examples to verify the effectiveness and practicability of the developed models and procedures.