A survey on pioneering metaheuristic algorithms between 2019 and 2024

With innovation accelerating, selecting the most effective algorithms has become increasingly demanding for researchers and practitioners alike. Recognizing this, we conducted an in-depth review of metaheuristics introduced in the past six years, focusing on their influence and effectiveness. We evaluated these algorithms across essential criteria: citation frequency, diversity in tackled problem types, code availability, ease of parameter tuning, introduction of novel mechanisms, and resilience to issues like stagnation and early convergence. Out of 158 algorithms, we identified 23 that set themselves apart, each contributing unique solutions to long-standing optimization challenges. These algorithms stand out for their versatility and innovation, positioning them as valuable assets for advancing research and addressing complex real-world problems. Our review offers a detailed analysis of these algorithms, comparing their strengths, limitations, similarities, and applications, while highlighting promising trends and future pathways in metaheuristic research.