Enhanced Fuzzy Clustering Algorithm and Cluster Validity Index for Human Perception

Abstract

In this study, we propose an enhanced fuzzy clustering algorithm related to a-cut interval descriptions of fuzzy numbers and a new cluster validity index, which occurs by a-cut intervals and adding two ad-hoc functions in the compactness and separability measures. As an application, we use the enhanced fuzzy clustering algorithm and its proposed validity index to rank supplier firms of a Turkish Machinery Corporation by design alternatives. In addition, the rankings of supplier firms are determined with a proposed decision measure. (C) 2012 Elsevier Ltd. All rights reserved.