TY - GEN
T1 - A new ranking methodology based on hierarchical cluster analysis
AU - Kabak, Özgür
AU - Ulengin, Füsun
AU - Önsel, Şule
PY - 2008
Y1 - 2008
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=60349103982&partnerID=8YFLogxK
U2 - 10.1109/ISKE.2008.4730956
DO - 10.1109/ISKE.2008.4730956
M3 - Conference contribution
AN - SCOPUS:60349103982
SN - 9781424421978
T3 - Proceedings of 2008 3rd International Conference on Intelligent System and Knowledge Engineering, ISKE 2008
SP - 360
EP - 365
BT - Proceedings of 2008 3rd International Conference on Intelligent System and Knowledge Engineering, ISKE 2008
T2 - Proceedings of 2008 3rd International Conference on Intelligent System and Knowledge Engineering, ISKE 2008
Y2 - 17 November 2008 through 19 November 2008
ER -