A Clustering Approach Using Cooperative Artificial Bee Colony Algorithm

Abstract

Artificial Bee Colony (ABC) is one of the most recently introduced algorithms based on the intelligent foraging behavior of a honey bee swarm. This paper presents an extended ABC algorithm, namely, the Cooperative Article Bee Colony (CABC), which significantly improves the original ABC in solving complex optimization problems. Clustering is a popular data analysis and data mining technique; therefore, the CABC could be used for solving clustering problems. In this work, first the CABC algorithm is used for optimizing six widely used benchmark functions and the comparative results produced by ABC, Particle Swarm Optimization (PSO), and its cooperative version (CPSO) are studied. Second, the CABC algorithm is used for data clustering on several benchmark data sets. The performance of CABC algorithm is compared with PSO, CPSO, and ABC algorithms on clustering problems. The simulation results show that the proposed CABC outperforms the other three algorithms in terms of accuracy, robustness, and convergence speed.

A Review on Artificial Bee Colony Algorithms and Their Applications to Data Clustering

“…The algorithm produced successful clustering results in comparison to other techniques. Z o u et al [158] modified the ABC by employing the cooperative strategy to find best solution with contribution of every individual. The final solutions are obtained in accordance with information from all individuals.…”

A Survey on Optimization Algorithms for Optimizing the Numerical Functions

“…Results show that the BSO with its two extensions performs best with respect to ABC algorithm. W.zou.et.al [7] introduces Cooperative ABC (CABC) for solving data clustering problems. Data clustering can be defined as the grouping of data into different clusters.…”

A review on Artificial Bee Colony algorithm

“…A cooperative ABC (CABC) algorithm was introduced by Zou et al [22]. In this work, the final solutions were produced by using the information from all the populations.…”