FSOA with cognitive ability
具有认知能力的捕鱼策略优化算法

In order to overcome the shortcoming of standard FSOA that was easily trapped in local optimum and had a low convergence rate in the late period, according to the fishing habit of fishers, this paper applied the fishers' cognitive ability in FSOA, and put forward an improving FSOA with cognitive ability. In this optimization algorithm, every fisher could estimate, according to his fishing experience and the state the group were being in, where was relatively thick with fish in comparison with the area around him. The experiment results show that this optimization algorithm has the great advantages of a rapid convergence rate and a high accurate numerical solution over standard FSOA, and can effectively avoid being trapped into local optimum.