Gases Brownian Motion Optimization: an Algorithm for Optimization (GBMO)
In recent years, different optimization methods have been developed for optimization problem. Many of these methods are inspired by swarm behaviors in nature. In this paper, a new algorithm for optimization inspired by the gases brownian motion and turbulent rotational motion is introduced, which is called Gases Brownian Motion Optimization (GBMO). The proposed algorithm is created using the features of gas molecules. The proposed algorithm is an efficient approach to search and find an optimum solution in search space. The efficiency of the proposed method has been compared with some well-known heuristic search methods. The obtained results confirm the high performance of the proposed method in solving various functions.
brownian motion turbulent rotational motion evolutionary algorithm optimization algorithm heuristic search algorithm kinetic energy satisfiability problem multimodal function unimodal function ideal gas law