An application of the generalised K-means algorithm in decision-making processes

Hsin-Hung Wu, Jiunn-I Shieh, Anthony Y.H. Liao and Shih-Yen Lin

International Journal of Operational Research, 2008, vol. 3, issue 1/2, 19-35

Abstract: A case study of applying the generalised K-means algorithm with different p values is provided to discuss the applicants' selection under a variety of criteria in an admission process. The properties of the generalised K-means algorithm are exploited in a decision-making process. When p is smaller and closer to zero, the results show the priorities are identical, which is to look for the applicants with even performance. In contrast, the most commonly used p values in K-means algorithm do not generate a systematic pattern. When p becomes larger and approaches ∞, the results show the priorities are difficult to tell, but the intention is to separate alternatives with a number of clusters, which is to look for the applicants with the greatest potential. Finally, in this case study, using smaller p values might provide stable priorities to select 21 applicants out of 36 participants.

Keywords: clusters; decision analysis; generalised K-means algorithm; priority; applicant selection; decision making. (search for similar items in EconPapers)
Date: 2008
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