Binary Water Stream Algorithm: A New Metaheuristic Optimization Technique
Faezeh Rahimi Sebdani, Mehdi Nasri · 2023
In recent years, the use of metaheuristic algorithms in solving optimization and data mining problems has been widely embraced. These algorithms have shown significant efficiency in solving complex and high-dimensional problems. The water flow algorithm, inspired by the natural movement of water towards the lowest possible point on the ground, has demonstrated remarkable superiority in solving continuous problems with high dimensions. However, it is not suitable for solving discrete and binary issues. In this article, the Water Stream Algorithm has been converted into a binary version using a combination of sigmoid and U-shaped transfer functions without changing operators. The statistical results show that the BWSTO algorithm has faster convergence and more robust exploitation than the Genetic Algorithm and Binary Particle Swarm Optimization Algorithm. This algorithm performs better than the Binary Gray Wolf Algorithm in avoiding local minima. The proposed algorithm has more exploratory capabilities compared to the binary gravitational search algorithm.