کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
384734 | 660854 | 2009 | 6 صفحه PDF | دانلود رایگان |
Clustering method is critical to market segmentation. In this paper, we proposed the immunity-based ant clustering algorithm, which integrates two search algorithms, the ant algorithm and the artificial immune system. Ant algorithm, a novel meta-heuristic approach for solving hard combinatorial optimization problems, is utilized to generate good solutions to the clustering problems. Then, the artificial immune system is adopted to search for optimization of clustering problems. Our proposed method is implemented to a real-world clustering problem of air-conditioner market segmentation in 3C chain store. Hypothesis tests are conducted to test the significance among our proposed method and other known clustering methods. As a result, IACA has the best clustering performance.
Journal: Expert Systems with Applications - Volume 36, Issue 3, Part 1, April 2009, Pages 4437–4442