Volume 23, Issue 2 (IJIEPM 2012)                   2012, 23(2): 239-249 | Back to browse issues page

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Sepehri M M, Kargari M. Improving the Customer Grouping Algorithm for Spare-Parts Distribution Using k-Means Tools. Journal title 2012; 23 (2) :239-249
URL: http://ijiepm.iust.ac.ir/article-1-884-en.html
Improving the Customer Grouping Algorithm for Spare-Parts Distribution Using k-Means Tools
Mohammad Mehdi Sepehri * , Mehrdad Kargari
Associate Professor, Industrial Engineering Department, Tarbiat Modares University , mehdi.sepehri@modares.ac.ir
Abstract:   (10299 Views)
Customer classification using k-means algorithm for optimizing the transportation plans is one of the most interesting subjects in the Customer Relationship Management context. In this paper, the real-world data and information for a spare-parts distribution company (ISACO) during the past 36 months has been investigated and these figures have been evaluated using k-means tool developed for spare-part demand similarity function in different regions of the country. Similarity function for customer behavior in different regions has been defined. Based on this function and with help of k-means algorithm, customers have been grouped and similar customers were put in the same groups. Customer similarity function has been developed through 5 steps and has been defined individually based on each factors of Euclidean distance, customer's order time and bulk value of the order. Then, these three factors have been combined and DCB function has been defined. In the final step, different weights have been allocated to different years and seasons and BCD function has been improved. The grouping process has been improved for three functions of Euclidean distance, DCB and BCD. This process was executed using the R software and the improved BCD function was recognized as the optimum grouping function. Then, using DMT model, customer behavior has been analyzed at each part and the proper distribution policies have been defined. Results indicate a significant cost reduction (32%) in spare-parts distribution costs for ISACO.
Keywords: Customer grouping algorithm, Customer Relationship Management, K-means, Similarity function, Spare-parts distribution
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Type of Study: Research | Subject: Other related Industrial and production reserach subjects in which has direct relation to the state-of-the art of the IE
Received: 2012/07/22 | Published: 2012/08/15
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