Abstract
Intuitionistic fuzzy sets are the most widely used fuzzy set extension in the literature. It is a fuzzy set extension in which decision makers specify the degree of membership of the elements in the set as well as their non-membership to the set. Thus, the indecision of the decision makers about the membership of the elements to the set also emerges spontaneously. It is known that discrete intuitionistic fuzzy sets or linear continuous intuitionistic fuzzy sets are used in the literature. In this study, it is aimed to develop non-linear continuous intuitionistic fuzzy sets and to use them in multi-criteria decision making models. CINFUSs consisting of membership and non-membership degrees represented by second-order non-linear functions, have been used to develop the analytical hierarchy process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodology in a fuzzy environment. This study is a milestone in showing how higher order non-linear functions can be used in intuitionistic fuzzy sets. The CINFUS-AHP&TOPSIS methodology has been applied to the solution of the multi-criteria research proposals evaluation for grand funding problem and has been tested for validity and robustness with sensitivity analysis and comparative analysis.
| Original language | English |
|---|---|
| Article number | 110579 |
| Journal | Applied Soft Computing |
| Volume | 145 |
| DOIs | |
| Publication status | Published - Sept 2023 |
Bibliographical note
Publisher Copyright:© 2023 Elsevier B.V.
Funding
With the developments in technology, the importance of research projects is increasing day by day. However, many people need financial support to implement their research projects. Grants are the most preferred financial tool by researchers, and almost all researchers seek a grant for their research projects. However, it is extremely important to choose the most appropriate research proposal, as grant fundings are limited and highly demanded. For this, the research evaluation group must determine a detailed selection of criteria to make an excellent decision [12] . Besides, the evaluation of research proposals for grant fundings is a complex problem with imprecise information. Therefore, the selection of an appropriate project proposal requires an MCDM model to be considered in a fuzzy environment. For this, first of all, it is necessary to determine the importance weights of the criteria to be considered in the selection of a suitable research proposal, and then to rank the alternative projects. In this context, a CINFUS-based hybrid MCDM model is proposed to obtain the best and most appropriate proposal among various options by complex and uncertain decision-making models in this study. In the study, firstly, the fuzzy extension of the AHP method in the CINFUS environment is presented in order to obtain the criterion weights in the uncertainty environment. Then, the CINFUS-based TOPSIS method has been developed to rank alternative projects. The effectiveness of the developed CINFUS-based methodology is presented on a case study based on the evaluation of research projects for grant funding.
| Funders | Funder number |
|---|---|
| Istanbul Teknik Üniversitesi | 44131 |
Keywords
- AHP
- CINFUS
- Continuous intuitionistic fuzzy sets
- Grant funding
- Multi-criteria decision making
- TOPSIS