Parallelized Artificial Bee Colony with Ripple-communication Strategy

Abstract

In this paper, a communication strategy for the parallelized Artificial Bee Colony (ABC) optimization is proposed for solving numerical optimization problems. The artificial agents are split into several independent subpopulations based on the original structure of the ABC, and the proposed communication strategy provides the information flow for the agents to communicate in different subpopulations. Three benchmark functions are used to test the behavior of convergence, the accuracy, and the speed of the proposed method. According to the experimental result, the proposed communicational strategy increases the accuracy of the ABC on finding the near best solution.