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A cloud-based and web-based group decision support system in multilingual environment with hesitant fuzzy linguistic preference relations

A cloud-based and web-based group decision support system in multilingual environment with hesitant fuzzy linguistic preference relations
A cloud-based and web-based group decision support system in multilingual environment with hesitant fuzzy linguistic preference relations

Due to the growing needs in decision-making under uncertainty, existing studies introduced consistency and consensus-driven algorithms for group decision-making (GDM) problems with hesitant fuzzy linguistic preference relations (HFLPRs). A decision support system (DSS) that can host these GDM algorithms to provide decision-support services or tools for practical use is urgently needed. However, the state-of-the-art architectures cannot organize these algorithms and related data to run within one framework. This is mainly due to the running environments for these GDM algorithms are different since these algorithms were not originally designed to be compatible. Given the multilingual consistency and consensus-based decision support algorithms, how to design and implement a cloud-based DSS in a multilingual environment is still an open question. To fill this gap, this paper provides a web-based and cloud-based DSS with a novel architecture that utilizes the advantages of microservices. The proposed system implements a multilingual support framework to dynamically upload, manage and run multilingual consistency and consensus-based decision support algorithms. An algorithm recommendation module is developed to help users choose suitable decision support algorithms. Tokenization is applied to deal with regulatory issues of knowledge protection, data privacy, and security while storing, analyzing, and transforming data into different algorithms for effective decision-making. An expert feedback study verified that our web and cloud-based DSS is a right artifact to fulfill the objective claimed in this paper.

cloud computing, decision support system, group decision making, hesitant fuzzy linguistic preference relation, pod-based architecture
0884-8173
5186-5216
Liu, Zixu
1b07df56-a07b-4e78-bebc-38657ca80f76
Han, Junyi
f9546a61-388f-4ba8-9520-e43b34f5b06f
Meng, Fanlin
3c9359f7-2fea-4477-a84c-3a283d3701dc
Liao, Huchang
6291d232-5410-49c5-8ed9-6eb4f9924599
Liu, Zixu
1b07df56-a07b-4e78-bebc-38657ca80f76
Han, Junyi
f9546a61-388f-4ba8-9520-e43b34f5b06f
Meng, Fanlin
3c9359f7-2fea-4477-a84c-3a283d3701dc
Liao, Huchang
6291d232-5410-49c5-8ed9-6eb4f9924599

Liu, Zixu, Han, Junyi, Meng, Fanlin and Liao, Huchang (2021) A cloud-based and web-based group decision support system in multilingual environment with hesitant fuzzy linguistic preference relations. International Journal of Intelligent Systems, 37 (8), 5186-5216. (doi:10.1002/int.22789).

Record type: Article

Abstract

Due to the growing needs in decision-making under uncertainty, existing studies introduced consistency and consensus-driven algorithms for group decision-making (GDM) problems with hesitant fuzzy linguistic preference relations (HFLPRs). A decision support system (DSS) that can host these GDM algorithms to provide decision-support services or tools for practical use is urgently needed. However, the state-of-the-art architectures cannot organize these algorithms and related data to run within one framework. This is mainly due to the running environments for these GDM algorithms are different since these algorithms were not originally designed to be compatible. Given the multilingual consistency and consensus-based decision support algorithms, how to design and implement a cloud-based DSS in a multilingual environment is still an open question. To fill this gap, this paper provides a web-based and cloud-based DSS with a novel architecture that utilizes the advantages of microservices. The proposed system implements a multilingual support framework to dynamically upload, manage and run multilingual consistency and consensus-based decision support algorithms. An algorithm recommendation module is developed to help users choose suitable decision support algorithms. Tokenization is applied to deal with regulatory issues of knowledge protection, data privacy, and security while storing, analyzing, and transforming data into different algorithms for effective decision-making. An expert feedback study verified that our web and cloud-based DSS is a right artifact to fulfill the objective claimed in this paper.

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Accepted/In Press date: 10 December 2021
e-pub ahead of print date: 28 December 2021
Additional Information: Funding Information: We wish to thank Long Jin for his support and contribution to implementing the DSS. The work was supported by the National Natural Science Foundation of China (71771156, 71971145, 72171158). Publisher Copyright: © 2021 Wiley Periodicals LLC.
Keywords: cloud computing, decision support system, group decision making, hesitant fuzzy linguistic preference relation, pod-based architecture

Identifiers

Local EPrints ID: 470664
URI: http://eprints.soton.ac.uk/id/eprint/470664
ISSN: 0884-8173
PURE UUID: d7045f17-291e-4457-be0b-008f8e295b6a
ORCID for Zixu Liu: ORCID iD orcid.org/0000-0002-4806-5482

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Date deposited: 17 Oct 2022 16:58
Last modified: 07 Jan 2023 05:03

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Contributors

Author: Zixu Liu ORCID iD
Author: Junyi Han
Author: Fanlin Meng
Author: Huchang Liao

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