Abstract
Swarm-based metaheuristic algorithms have bridged the gap from ideal situation to reality. They have been successful in removing the limitations of conventional methods by providing optimal and sub-optimal solutions to those optimisation problems which were earlier considered next to impossible. Their characteristics such as self-organisation and decentralisation have led to these advancements in literature. In this paper, the performance of one such nature inspired algorithm namely the bat algorithm has been tabulated on the basis of precision and convergence speed. The conclusions drawn from the performance and observations are also described later.
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