Proceedings of the 2019 International Conference on Modeling, Simulation and Big Data Analysis (MSBDA 2019)

Evaluation of the Ordered Weighted Averaging Method

Authors
Jizhong Zhu, Min Fei
Corresponding Author
Jizhong Zhu
Available Online August 2019.
DOI
10.2991/msbda-19.2019.27How to use a DOI?
Keywords
Ordered weighted averaging operator, analytic hierarchical process, fuzzy linguistic quantifiers, minimal variability, Decision-making
Abstract

This paper discusses and evaluates the ordered weighted averaging (OWA) approach. OWA is one of the decision-making methods. The order weights of OWA are key factors that make the decision for the given slections. There are several approaches to determine the order weights such as the minimal variability mean and the fuzzy linguistic quantifier method. This short paper proposes to use an analytic hierarchical process (AHP) to solve the same decision-making issue as OWA analyzed. A water resources management problem is selected as testing example. The simulation results shown that the proposed AHP based approach can obtain the best results.

Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2019 International Conference on Modeling, Simulation and Big Data Analysis (MSBDA 2019)
Series
Advances in Computer Science Research
Publication Date
August 2019
ISBN
10.2991/msbda-19.2019.27
ISSN
2352-538X
DOI
10.2991/msbda-19.2019.27How to use a DOI?
Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Jizhong Zhu
AU  - Min Fei
PY  - 2019/08
DA  - 2019/08
TI  - Evaluation of the Ordered Weighted Averaging Method
BT  - Proceedings of the 2019 International Conference on Modeling, Simulation and Big Data Analysis (MSBDA 2019)
PB  - Atlantis Press
SP  - 171
EP  - 174
SN  - 2352-538X
UR  - https://doi.org/10.2991/msbda-19.2019.27
DO  - 10.2991/msbda-19.2019.27
ID  - Zhu2019/08
ER  -