International Journal of Computational Intelligence Systems

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Volume 11, Issue 1, 2018, Pages 451 - 468

The analytic hierarchy process with personalized individual semantics

Authors
Qiuxiang Zhou1, qxzhou@stu.scu.edu.cn, Yucheng Dong1, ycdong@scu.edu.cn, Hengjie Zhang2, *, hengjiezhang@hhu.edu.cn, Yuan Gao1, gaoyuan1984@scu.edu.cn
1Business School, Sichuan University, Chengdu 610065, China
2Business School, Hohai University, Nanjing 211100, China
* Corresponding author
Corresponding Author
Received 25 July 2017, Accepted 22 December 2017, Available Online 1 January 2018.
DOI
10.2991/ijcis.11.1.34How to use a DOI?
Keywords
Analytic hierarchy process (AHP); personalized individual semantics (PIS); numerical scale; the 2-tuple linguistic model; consistency-driven methodology
Abstract

Personalized individual semantics (PIS) is not unusual in our daily life, and it has an important influence on the final decision results in linguistic decision making. The analytic hierarchy process (AHP) has now become a popular decision tool because of its sound mathematical design and ease of applicability to real-world decision making problems. In the AHP, two formats of preference information are included: linguistic and numerical preference information. In order to implement the computation operation, the linguistic preference information is often transformed into the numerical preference information using a fixed numerical scale function (e.g., the Saaty scale). However, the PIS is not taken into account by the AHP with a fixed numerical scale function. Therefore, this study proposes a novel AHP framework with the PIS, and develops a consistency-driven methodology to minimize the inconsistency level of numerical preference information that transformed from linguistic preference information. In the proposed AHP framework, a two-stage based optimization model is designed to deal with the PIS, and the proposed optimization models are converted into some linear programming models that can be easily solved. Finally, a practical example and a comparison experiment are proposed to verify the validity of our proposal.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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<Previous Article In Issue
Next Article In Issue>
Journal
International Journal of Computational Intelligence Systems
Volume-Issue
11 - 1
Pages
451 - 468
Publication Date
2018/01/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.11.1.34How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - Qiuxiang Zhou
AU  - Yucheng Dong
AU  - Hengjie Zhang
AU  - Yuan Gao
PY  - 2018
DA  - 2018/01/01
TI  - The analytic hierarchy process with personalized individual semantics
JO  - International Journal of Computational Intelligence Systems
SP  - 451
EP  - 468
VL  - 11
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.11.1.34
DO  - 10.2991/ijcis.11.1.34
ID  - Zhou2018
ER  -