Research on Modified Artificial Bee Colony Clustering Algorithm

In order to overcome the disadvantages of the KMeans Clustering algorithm, such as the poor global search ability, being sensitive to initial cluster centric, as well as the vulnerable to trap in local optima and the slow convergence velocity in later period of the original Artificial Bee Colony (ABC) algorithm, a Modified ABC algorithm was proposed. Modified Artificial Bee Colony algorithm combined with K-means Clustering algorithm, named it as MABC-K-means algorithm, to establish Hybrid algorithm for solving framework. Through extensive testing, the MABC-K-means algorithm can improve cluster performance effectively. Finally, according to optimization solution strategy, instantiate Customer Relationship Management issue in the process of instantiating framework.