A Market Segmentation System for Consumer Electronics Industry Using Particle Swarm Optimization and Honey Bee Mating Optimization

A clustering system which integrated particle swarm optimization and honey bee mating optimization methods is proposed, which can effectively find the global optimum solution, and extend the application of market segmentation to solve the RFM model.

Abstract

The use of information technologies in various business areas is emerging in recent years. With the development of information technology, how to find useful information existed in vast data has become an important issue. The most broadly discussed technique is data mining, which has been successfully applied to many fields and analytic tools. Clustering analysis which tries to segment data into homogeneous clusters is one of the most useful technologies in data mining methods. Market segmentation is among the important issue of most companies. Market segmentation relies on the data clustering in a huge data set. In this study, we propose a clustering system which integrated particle swarm optimization and honey bee mating optimization methods. Simulations for a benchmark test functions show that our proposed method possesses better ability to find the global optimum than other well-known clustering algorithms. The results show that system through PSHBMO can effectively find the global optimum solution, and extend the application of market segmentation to solve the RFM model.