Izvorni znanstveni članak
https://doi.org/10.1080/1331677X.2021.2025125
Granular computing and optimization model-based method for large-scale group decision-making and its application
Yuanhang Zheng
Zeshui Xu
Yuhang Tian
Sažetak
In large-scale group decision-making process, some decision makers hesitate among several linguistic terms and cannot compare
some alternatives, so they often express evaluation information
with incomplete hesitant fuzzy linguistic preference relations.
How to obtain suitable large-scale group decision-making results
from incomplete preference information is an important and
interesting issue to concern about. After analyzing the existing
researches, we find that: i) the premise that complete preference
relation is perfectly consistent is too strict, ii) deleting all incomplete linguistic preference relations that cannot be fully completed will lose valid assessment information, iii) semantics given
by decision makers are greatly possible to be changed during the
consistency improving process. In order to solve these issues, this
work proposes a novel method based on Granular computing
and optimization model for large-scale group decision-making,
considering the original consistency of incomplete hesitant fuzzy
linguistic preference relation and improving its consistency without changing semantics during the completion process. An illustrative example and simulation experiments demonstrate the
rationality and advantages of the proposed method: i) semantics
are not changed during the consistency improving process, ii)
completion process does not significantly alter the inherent quality of information, iii) complete preference relations are globally
consistent, iv) final large-scale group decision-making result is
acquired by fusing complete preference relations with different weights.
Ključne riječi
Large-scale group decisionmaking; granular computing; optimization model; incomplete hesitant fuzzy linguistic preference relation.
Hrčak ID:
302797
URI
Datum izdavanja:
31.3.2023.
Posjeta: 165 *