As a new and competitive population-based optimization algorithm, the Whale Optimization
Algorithm (WOA) outperforms some other biological-inspired algorithms from the perspective …

Moth flame optimization (MFO) algorithm is a relatively new nature-inspired optimization
algorithm based on the moth's movement towards the moon. Premature convergence and …

The sine cosine algorithm (SCA) is a relatively novel population-based optimization
technique that has been proven competitive with other algorithms and it has received …

Abstract Whale Optimization Algorithm (WOA), as a new population-based optimization
algorithm, performs well in solving optimization problems. However, when tackling high …

The metaheuristic algorithms do not depend on the functional form when solving the
optimization problem. They have strong adaptability and are widely used in many fields …

The self-organizing migrating algorithm (SOMA) is a population-based meta-heuristic that
belongs to swarm intelligence. In the last 20 years, we can observe two main streams in the …

In numerous real-life applications, nature-inspired population-based search algorithms have
been applied to solve numerical optimization problems. This paper focuses on a simple and …

Meta-heuristic algorithms are widely viewed as feasible techniques to solve continuous
large-scale numerical optimization problems. Grey wolf optimizer (GWO) is a relatively new …

State transition algorithm (STA) is an efficient and powerful metaheuristic method for solving
global optimization problems, and it has been successfully applied in many engineering …

This paper presents a new algorithm for optimizing parameters in swarm algorithm using
reinforcement learning. The algorithm, called iSOMA-RL, is based on the iSOMA algorithm …