Rapid industrialization has fueled the need for effective optimization solutions, which has led to the widespread use of meta-heuristic algorithms. Among the repertoire of over 600, over 300 new methodologies have been developed in the last ten years. This increase highlights the need for a sophisticated grasp of these novel methods. The use of biological and natural phenomena to inform meta-heuristic optimization strategies has seen a paradigm shift in recent years. The observed trend indicates an increasing acknowledgement of the effectiveness of bio-inspired methodologies in tackling intricate engineering problems, providing solutions that exhibit rapid convergence rates and unmatched fitness scores. This study thoroughly examines the latest advancements in bio-inspired optimisation techniques. This work investigates each method’s unique characteristics, optimization properties, and operational paradigms to determine how revolutionary these approaches could be for problem-solving paradigms. Additionally, extensive comparative analyses against conventional benchmarks, such as metrics such as search history, trajectory plots, and fitness functions, are conducted to elucidate the superiority of these new approaches. Our findings demonstrate the revolutionary potential of bio-inspired optimizers and provide new directions for future research to refine and expand upon these intriguing methodologies. Our survey could be a lighthouse, guiding scientists towards innovative solutions rooted in various natural mechanisms.
ORCID: 
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)