Development of a scenario-based fuzzy robust decision support system

Purpose: The purpose of this research is providing a solution to help make better decisions in the ambiguous world of uncertainties. In a world full of uncertainties, researchers invented methods such as scenario planning and robust decision making, and for highly ambiguous environments they tough up fuzzy logic. Today, without a decision support system, decision making will be done relatively slowly. Without considering different scenarios, it is not possible to make robust decisions in the face of numerous large and small uncertainties.Methodology: This research is of applied and qualitative type. The data were collected in a documentary and library method from the articles and books available in reliable scientific databases using computer files. The type of data is qualitative and the method of data analysis is thematic analysis.Findings: In robust decision-making, scenarios are used in two ways. In one case, after choosing several alternative decisions, you can write the scenarios that affect them and evaluate the decisions. Otherwise, you can first write different scenarios and then test alternative decisions in those scenarios and choose the optimal decision as the robust decision. Also, fuzzy logic can be used in the form of fuzzy Delphi and other fuzzy calculations in different parts of scenario planning and strategy robustness evaluation.Originality/Value: In this paper, a method was presented according to which a robust decision support system can be developed using the GBN scenario planning method and fuzzy logic. In this method, fuzzy Delphi was used to create scenarios and fuzzy inference system was used to make decisions.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-12-01
DOI
https://doi.org/10.22105/dmor.2024.476625.1869
Primary Topic
Multi-Criteria Decision Making
Type
article
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article

Development of a scenario-based fuzzy robust decision support system

SHILAP Revista de lepidopterología
Multi-Criteria Decision Making
article

Development of a scenario-based fuzzy robust decision support system

article en

Abstract

Purpose: The purpose of this research is providing a solution to help make better decisions in the ambiguous world of uncertainties. In a world full of uncertainties, researchers invented methods such as scenario planning and robust decision making, and for highly ambiguous environments they tough up fuzzy logic. Today, without a decision support system, decision making will be done relatively slowly. Without considering different scenarios, it is not possible to make robust decisions in the face of numerous large and small uncertainties.Methodology: This research is of applied and qualitative type. The data were collected in a documentary and library method from the articles and books available in reliable scientific databases using computer files. The type of data is qualitative and the method of data analysis is thematic analysis.Findings: In robust decision-making, scenarios are used in two ways. In one case, after choosing several alternative decisions, you can write the scenarios that affect them and evaluate the decisions. Otherwise, you can first write different scenarios and then test alternative decisions in those scenarios and choose the optimal decision as the robust decision. Also, fuzzy logic can be used in the form of fuzzy Delphi and other fuzzy calculations in different parts of scenario planning and strategy robustness evaluation.Originality/Value: In this paper, a method was presented according to which a robust decision support system can be developed using the GBN scenario planning method and fuzzy logic. In this method, fuzzy Delphi was used to create scenarios and fuzzy inference system was used to make decisions.

SHILAP Revista de lepidopterología
Imam Khomeini International University (IR)
Peace, Justice and strong institutions
Openalex Percentile: Top 47%
Multi-Criteria Decision Making
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Development of a scenario-based fuzzy robust decision support system · SHILAP Revista de lepidopterología (2024) | TGRS Research Map | TGRS