A new ranking methodology based on hierarchical cluster analysis

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IEEE

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info:eu-repo/semantics/closedAccess

Özet

This paper provides a methodology to rank competing entities in terms of their overall performance. Similarities of the entities are used for ranking. The methodology is composed of three stages. Initially, the data is standardized. Secondly, hierarchical cluster analysis is conducted to capture the similarities among the entities. Then a linear programming model is run for final rankings. Furthermore a benchmark example with sensitivity analysis is given to illustrate the methodology and to show its applicability.

Açıklama

Ülengin, Füsun (Dogus Author) -- Önsel, Şule (Dogus Author) -- Conference full title: 2008 3rd International Conference on Intelligent System and Knowledge Engineering, ISKE 2008; Xiamen; China; 17 November 2008 through 19 November 2008

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Decision Making, Linear Programming, Pattern Clustering, Sensitivity Analysis

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2008 3rd International Conference on Intelligent System and Knowledge Engineering

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1

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Kabak, Ö., Ülengin, F., & Önsel, Ş. (2008). A new ranking methodology based on hierarchical cluster analysis. In 2008 3rd International Conference on Intelligent System and Knowledge Engineering (ISKE) (Volume 1) (pp. 360-365). Piscataway, NJ: IEEE. https://dx.doi.org/10.1109/ISKE.2008.4730956

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