A Method for Determining the Relative Importance in AHP Using Logarithmic Fuzzy Numbers
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- KURASHIGE Kenji
- Faculty of Computer Science and System Engineering, Okayama Prefectural University
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- KAMEYAMA Yoshimasa
- Faculty of Computer Science and System Engineering, Okayama Prefectural University
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- MIYAZAKI Shigeji
- Faculty of Engineering Okayama University
Bibliographic Information
- Other Title
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- AHPにおける対数型ファジィ数を用いた相対的重要度決定法
- AHP ニ オケル タイスウガタ ファジィスウ オ モチイタ ソウタイテキ ジュウヨウド ケッテイホウ
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Abstract
The Analytic Hierarchy Process (AHP) is used for decision-making with difficult quantification. In AHP, we decide the relative importance of each criteria and alternative, and modifiers, such as "Weak" or "Strong" are used for pairwise comparison. In this paper, we propose a method for determining relative importance by using fuzzy numbers which represent the feelings of the decision maker. In the conventional AHP, a numerical value for the modifier, which increases linearly from one to nine, is used. However, in this paper, it is assumed that the numerical value of the modifier increases exponentially. Therefore, the fuzzy numbers are expressed using a logarithmic scale. The procedure in this paper is as follow. Firstly, the numerical value applied to each modifier and the sufficiently satisfactory range of each value are informed to the decision maker. Secondly, the membership functions of the fuzzy numbers are created by these values on a logarithmic scale. Finally, the membership functions are formulated into a fuzzy linear planning problem and the relative importance of each element is calculated. Moreover, we propose a method for application to group decisionmaking. The proposed method is compared with conventional methods by numerical experiment, and the efficiency of the proposed method is shown.
Journal
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- Journal of Japan Industrial Management Association
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Journal of Japan Industrial Management Association 50 (4), 216-225, 1999
Japan Industrial Management Association
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Keywords
Details 詳細情報について
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- CRID
- 1390282680481274112
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- NII Article ID
- 110003945540
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- NII Book ID
- AN10561806
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- ISSN
- 21879079
- 13422618
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- NDL BIB ID
- 4877759
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- CiNii Articles
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- Abstract License Flag
- Disallowed