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A probabilistic multiple criteria sorting approach based on distance functions
Date
2015-05-01
Author
ÇELİK, BİLGE
Karasakal, Esra
İyigün, Cem
Metadata
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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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BibTeX
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.