Parallelized Flower Pollination Algorithm with a Communication Strategy

Parallel processing is an essential requirement for optimum computations in modern equipment. In this paper, a communication strategy for the parallelized Flower Pollination Algorithm is proposed for solving numerical optimization problems. In this proposed method, the population flowers are split into several independent groups based on the original structure of the Flower Pollination Algorithm (FPA), and the proposed communication strategy provides the information flow for the flowers 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 FPA on finding the best solution is up to 78% in comparison with original method.