A new ranking methodology based on hierarchical cluster analysis
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KünyeKabak, 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. http://dx.doi.org/10.1109/ISKE.2008.4730956
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.