New Metaheuristic

Metaheuristics are advanced computational methods designed to efficiently solve complex optimization problems, often surpassing the capabilities of traditional algorithms. Current research focuses on developing novel metaheuristics inspired by diverse natural phenomena (e.g., animal behavior, biological processes), leveraging AI tools like large language models for automated algorithm design, and enhancing existing algorithms like genetic algorithms through techniques such as randomized repair and Gaussian mutation. These improvements aim to enhance the performance, robustness, and applicability of metaheuristics across various fields, from engineering design and resource management to medical diagnosis and environmental modeling.