Simulated Rain Algorithm: A new metaheuristic method for optimization problems

Abstract

This paper presents a new heuristic method named simulated rain algorithm (SRA) for global optimization problems. The SRA simulates the steps of rainfall in nature, such as the splitting and merging of raindrops and the formation of rain water. And then, based on these steps, an effective mechanism is derived to solve the global optimal problem. Finally, the performance of SRA is benchmarked on 8 classical test functions, and the experimental results validate the effectiveness of the proposed simulated rain algorithm.