Nature‐Inspired Algorithms for Computational Intelligence Theory—A State‐of‐the‐Art Review
Akoramurthy Balasubramaniam, K. Dhivya, B. Surendiran · 2024
The history of computational intelligence can be traced back to several decades ago. Several technologies such as evolutionary computation, neural networks, and fuzzy systems were fused together to be called CI technologies. Nature-inspired algorithms, which are more adaptable and effective at addressing optimization issues, have changed over time. Many different types of nature-inspired algorithms are now being developed, and the majority of them are focused on self-organizing communities of nature and optimization issues. This article gives a state-of-the-art assessment of a few popular optimization techniques. Its key traits have been examined and compared to other established methods like gradient-based and gradient-free algorithms. Additionally, certain unresolved issues with optimization and metaheuristics methods were identified, which should be helpful for further work.