Snowflake optimization algorithm

In recent years, especially in the solution of engineering problems, optimization is frequently used. In particular, heuristic optimization techniques have become popular in solving these problems. Therefore, many heuristic optimization techniques have been developed in the literature for this purpose. In this thesis, a new heuristic optimization algorithm is proposed that can be used to solve optimization problems. The proposed algorithm is based on snowfall. According to the algorithm, the advent of snowflakes in order to reach the surface of the earth from the sky is modeled as searching for the best in terms of optimization. The developed algorithm is called Snowflake Optimization Algorithm. In this thesis, the fundamentals of this algorithm, working principle and formulations are presented in detail. In addition, the effectiveness of SFO was tested using thirteen benchmark functions from the literature. The results showed that the algorithm was successful in solving these functions.