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.

Solving SAT problem in continue space is not as easy as solving this problem in discrete space. But GBMO has good performance for solving this problem in continue space. The obtained results confirm the high performance of the proposed method in solving various functions and SAT problems. GBMO is more successful than the other compared algorithms for optimization problems with high dimensions because of powerful exploration technique in the gases Brownian movement.Figure optionsDownload as PowerPoint slideHighlights
► A new algorithm for optimization inspired by the gases brownian motion and turbulent rotational motion is introduced.
► 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 obtained results confirm the high performance of the proposed method in solving various functions.