A probabilistic multiple criteria sorting approach based on distance functions

Date

2015-05-01

Author

ÇELİK, BİLGE
Karasakal, Esra
İyigün, Cem

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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In this paper, a new probabilistic distance based sorting (PDIS) method is developed for multiple criteria sorting problems. The distance to the ideal point is used as a criteria disaggregation function to determine the values of alternatives. These values are used to sort alternatives into the predefined classes. The method also calculates probabilities that each alternative belong to the predefined classes in order to handle alternative optimal solutions. It is applied to five data sets and its performance is compared with two well-known methods from literature. Computational experiments show that the PDIS method performs better than the other methods.

Subject Keywords

Multiple criteria sorting, Probabilistic sorting, Distance function based sorting

URI

https://hdl.handle.net/11511/40041

Journal

EXPERT SYSTEMS WITH APPLICATIONS

DOI

https://doi.org/10.1016/j.eswa.2014.11.049

Collections

Department of Industrial Engineering, Article

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Citation Formats

B. ÇELİK, E. Karasakal, and C. İyigün, “A probabilistic multiple criteria sorting approach based on distance functions,” EXPERT SYSTEMS WITH APPLICATIONS, pp. 3610–3618, 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/40041.