The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
TOPSIS Based Nonlinear Programming Methodology for Multiattribute Decision Making With Interval-Valued Intuitionistic Fuzzy Sets
Abstract
Interval-valued intuitionistic fuzzy (IVIF) sets are useful to deal with fuzziness inherent in decision data and decision-making processes. The aim of this paper is to develop a nonlinear-programming methodology that is based on the technique for order preference by similarity to ideal solution to solve multiattribute decision-making (MADM) problems with both ratings of alternatives on attributes and weights of attributes expressed with IVIF sets. In this methodology, nonlinear-programming models are constructed on the basis of the concepts of the relative-closeness coefficient and the weighted-Euclidean distance. Simpler auxiliary nonlinear-programming models are further deduced to calculate relative-closeness of IF sets of alternatives to the IVIF-positive ideal solution, which can be used to generate the ranking order of alternatives. The proposed methodology is validated and compared with other similar methods. A real example is examined to demonstrate the applicability and validity of the methodology proposed in this paper.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Atanassov, K. T. (1986) · Fuzzy Sets and Systems · doi:10.1016/s0165-0114(86)80034-3 · Cited by 16,465
Cited by
A state-of the-art survey of TOPSIS applications
Behzadian, M., Khanmohammadi Otaghsara, S., Yazdani, M., & Ignatius, J. (2012) · Expert Systems with Applications · doi:10.1016/j.eswa.2012.05.056 · Cited by 2,690
Hesitant Fuzzy Linguistic Term Sets for Decision Making
Rodriguez, R. M., Martinez, L., & Herrera, F. (2012) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2011.2170076 · Cited by 2,328
Zavadskas, E. K., Mardani, A., Turskis, Z., Jusoh, A., & Nor, K. M. (2016) · International Journal of Information Technology & Decision Making · doi:10.1142/s0219622016300019 · Cited by 485
Liu, P. (2014) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2013.2248736 · Cited by 403
Li, D.-F. (2010) · Computers & Mathematics with Applications · doi:10.1016/j.camwa.2010.06.039 · Cited by 366
Metadata
- Authors
- Li
- Venue
- IEEE Transactions on Fuzzy Systems
- Published
- 2010
- ISSN
- 1063-6706 (ISSN-L)
- 1941-0034
- OpenAlex
- W2116321937
- Cited by
- 397
- References
- 1
- FWCI
- 33.57
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: TOPSIS Based Nonlinear Programming Methodology for Multiattribute Decision Making With Interval-Valued Intuitionistic Fuzzy Sets. https://app.cochat.ai/papers/10.1109/tfuzz.2010.2041009
- The paper
- Li. (2010). TOPSIS Based Nonlinear Programming Methodology for Multiattribute Decision Making With Interval-Valued Intuitionistic Fuzzy Sets. IEEE Transactions on Fuzzy Systems. https://doi.org/10.1109/tfuzz.2010.2041009
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
