Applying artificial immune system and ant algorithm in air-conditioner market segmentation

Authors:
Chui-Yu Chiu;I-Ting Kuo;Chia-Hao Lin
Affiliations:
Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei 106, Taiwan, ROC;Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei 106, Taiwan, ROC;Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei 106, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

Citing 9
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Abstract

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.