Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/30539
Title: Customer grouping for better resources allocation using GA based clustering technique
Authors: Ho, GTS
Ip, WH 
Lee, CKM
Mou, WL
Keywords: Customer grouping
Genetic algorithms
k-Means
Resource allocation
Issue Date: 2012
Publisher: Pergamon Press
Source: Expert systems with applications, 2012, v. 39, no. 2, p. 1979-1987 How to cite?
Journal: Expert systems with applications 
Abstract: Appropriate organizational resources allocation becomes a major challenge for companies to address the rapid demands for resources from different operational aspects while resource utilization is keeping low. Differentiate exiting customers with common features into smaller groups can serve as a piece of useful reference for decision-making. So far, k-means algorithm is the most commonly used clustering technique for conducting customer grouping. However, k-means limits the grouping consideration to a fixed number of dimensions among each group and the grouping results are significantly influenced by the initial clusters means. In this research, a robust genetic algorithm (GA) based k-means clustering algorithm is proposed in attempt to classify existing customers of the enterprise into groups with consideration of relevant attributes for the sake of obtaining desirable grouping results in an efficient manner. Different from k-means, the proposed GA-based k-means algorithm is able to select which and how many dimensions are better to be considered for each customer group when developing approximate optimal solutions. A case study is conducted on a window curtain manufacturer with the application of software Generator associated with MS Excel.
Description: This Special Issue includes a set of expanded papers published in the proceedings of the 9th Mexican International Conference on Artificial Intelligence (MICAI-2010) celebrated in Pachuca Hidalgo, México from November 8 to 13, 2010.
URI: http://hdl.handle.net/10397/30539
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2011.08.045
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

20
Last Week
0
Last month
1
Citations as of Jun 18, 2017

WEB OF SCIENCETM
Citations

11
Last Week
0
Last month
1
Citations as of Jun 18, 2017

Page view(s)

31
Last Week
4
Last month
Checked on Jun 18, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.