Parallelized bat algorithm with a communication strategy

Abstract

The trend in parallel processing is an essential requirement for optimum computations in modern equipment. In this paper, a communication strategy for the parallelized Bat Algorithm optimization is proposed for solving numerical optimization problems. The population bats are split into several independent groups based on the original structure of the Bat Algorithm (BA), and the proposed communication strategy provides the information flow for the bats to communicate in different groups. Four 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 BA on finding the near best solution.