International Journal of Computational Intelligence Systems

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Volume 13, Issue 1, 2020, Pages 130 - 141

Optimisation of Group Consistency for Incomplete Uncertain Preference Relation

Authors
Xiujuan Ma1, Zaiwu Gong1, 2, *, Weiwei Guo1
1School of Management Science and Engineering, Nanjing University of Information Science and Technology, No. 219, Ningliu Road, Nanjing, Jiangsu 210044, China
2School of Business, Linyi University, Shuangling Road, Linyi, Shandong 276000, China
*Corresponding author. E-mail: zwgong26@163.com
Corresponding Author
Zaiwu Gong
Received 6 October 2019, Accepted 8 December 2019, Available Online 30 January 2020.
DOI
10.2991/ijcis.d.200121.002How to use a DOI?
Keywords
Incomplete preference relation; Group decision making; Additive consistency; Uncertainty theory
Abstract

An incomplete uncertain preference relation (UPR) is typical in group decision making (GDM) for decision makers (DMs) to express preference over alternatives because of the information interaction barrier between people and decision making environment. Completing missing values can guarantee individual consistency and consensus level effectively. The operation of traditional interval preference relations (IPRs) is based only on the end point transformation, which may cause interval discretisation and information distortion easily. To overcome these limitations, pairwise comparison of alternatives in an IPR is treated as an uncertain distribution function of the subjective preference of the DM which avoids discretisation operation and handles interval numbers collectively. A belief degree is used to maintain the original information as much as possible. It guarantees the extent how people believe the estimated value is close to the incomplete original value. An uncertain chance constrained programming model is proposed herein to estimate incomplete values based on a belief degree when the preference relation obeys a linear uncertain distribution. A distance measure is defined to compute the consistency index and consensus degree. Subsequently, an iterative algorithm is presented for GDM with linear UPRs, which adjusts inconsistent preference relations and uses an operator to aggregate all individual preference relations. Furthermore, it is proven that the operation of UPRs is an extension of that of traditional IPRs under a certain belief degree.

Copyright
© 2020 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/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
13 - 1
Pages
130 - 141
Publication Date
2020/01/30
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.d.200121.002How to use a DOI?
Copyright
© 2020 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - Xiujuan Ma
AU  - Zaiwu Gong
AU  - Weiwei Guo
PY  - 2020
DA  - 2020/01/30
TI  - Optimisation of Group Consistency for Incomplete Uncertain Preference Relation
JO  - International Journal of Computational Intelligence Systems
SP  - 130
EP  - 141
VL  - 13
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.200121.002
DO  - 10.2991/ijcis.d.200121.002
ID  - Ma2020
ER  -