Study of Parallel Model of Artificial Bee Colony Algorithm

Abstract

The paper presents the exploration of artificial bee colony optimization algorithm for multidimension functions which is implemented in Python 3. Due to increase of the searching complexity, the high dimensional applied problems require development of the concurrent computing approaches which involve either parallel or asynchronous programming. The latter causes growth of general runtime and becomes bottleneck of single-processing implementation. In order to deal with the raised issue, we propose the parallelization algorithms based on multiprocessing library. The developed parallel approaches have shown the significant increase of the performance and allow taking into account multi-dimensional character of optimization problems. Despite the limitation of Python 3 multi-threading capabilities and the computational cost of creating execution processes, the proposed and explored approaches have demonstrated their efficiency for a number of benchmark functions.