具有认知能力的捕鱼策略优化算法

FSOA with cognitive ability

针对捕鱼策略优化方法在处理复杂优化问题时易陷入局部极值,且后期收敛速度慢的缺陷,根据现实中渔夫的捕鱼习惯,将渔夫的认知能力应用到基本FSOA中,提出了一种改进的具有认知能力的捕鱼策略优化方法(CAFSOA)。该算法中的渔夫可根据其前期捕鱼经验和当前群体状况来判断何处鱼的浓度比较高。实验结果表明,该优化方法具有较快的收敛速度和较好的优化精度,能有效地避免早熟收敛问题。

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.