×

Evaluation of investment opportunities with interval-valued fuzzy TOPSIS method. (English) Zbl 1506.91042

Summary: The purpose of this study is extended the TOPSIS method based on interval-valued fuzzy set in decision analysis. After the introduction of TOPSIS method by Hwang and Yoon in 1981, this method has been extensively used in decision-making, rankings also in optimal choice. Due to this fact that uncertainty in decision-making and linguistic variables has been caused to develop some new approaches based on fuzzy-logic theory. Indeed, it is difficult to achieve the numerical measures of the relative importance of attributes and the effects of alternatives on the attributes in some cases. In this paper to reduce the estimation error due to any uncertainty, a method has been developed based on interval-valued fuzzy set. In the suggested TOPSIS method, we use Shannon entropy for weighting the criteria and apply the Euclid distance to calculate the separation measures of each alternative from the positive and negative ideal solutions to determine the relative closeness coefficients. According to the values of the closeness coefficients, the alternatives can be ranked and the most desirable one(s) can be selected in the decision-making process.

MSC:

91B06 Decision theory
91B86 Mathematical economics and fuzziness

References:

[1] S. Ballı and S. Korukoğlu (2009), “Operating SystemSelection Using Fuzzy AHP and Topsis Methods”, Mathematical & Computational Applications, 14 (2), 119-130. · Zbl 1168.90497
[2] C.L. Hwang, K. Yoon, Multiple Attributes Decision Making Methods and Applications, Springer, Berlin Heidelberg, 1981. · Zbl 0453.90002
[3] C.T. Chen, Extensions of the TOPSIS for group decision-making under fuzzy environment, Fuzzy Sets and Systems 114 (2000) 1-9. · Zbl 0963.91030
[4] D. Dubois, S. Gottwald, P. Hajek, J. Kacprzyk and H. Prade, Terminological difficulties in fuzzy set theory—the case of “intuitionistic fuzzy sets”, Fuzzy Sets and Systems 156 (2005) 485-491. · Zbl 1098.03061
[5] D.H. Hong and S. Lee, Some algebraic properties and a distance measure for intervalvalued fuzzy numbers, Information Sciences 148 (2002) 1-10. · Zbl 1019.03036
[6] K. Yoon, System selection by multiple attribute decision making, Ph.D. dissertations, Kansas State University, Manhattan, Kansas, 1980.
[7] L. Zadeh, The concept of a linguistic variable and its application to approximate reasoning - I, Information Science 8 (1975) 199-249. · Zbl 0397.68071
[8] L.A. Zadeh, the concept of a linguistic variable and its application to approximate reasoning—I, Inform. Sci. 8 (1975) 199-249. · Zbl 0397.68071
[9] M.B. Gorzalczany, A method of inference in approximate reasoning based on interval-valued fuzzy sets, Fuzzy Sets and Systems 21 (1987) 1-17. · Zbl 0635.68103
[10] P. Grzegorzewski, Distances between intuitionistic fuzzy sets and/or intervalvalued fuzzy sets based on the Hausdorff metric, Fuzzy Set and Systems 148 (2004) 319-328. · Zbl 1056.03031
[11] Şenel, M., Şenel, B., Havle, C.A., (2018). Risk Analysis of Ports in Maritime Industry in Turkey Using FMEA Based Intuitionistic Fuzzy Topsis Approach, ITM Web of Conference, 01023 (8). DOI: https://doi.org/10.1051/itmconf/2018221023.
[12] M. Şenel, B. Şenel, Havle, C.A., (2018). Analysis of APSP Key Factors By Using Fuzzy Cognitive Map(FCM), Safety Science, (Yayınaşamasında).
[13] Şenel, B., Şenel, M., Aydemir, G., (2018). Use and Comparison of TOPSIS and Electre Methods in Personnel Selection. ITM Web of Conference, 01021 (10). DOI: https://doi.org/10.1015/itmconf/20182201021.
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.