基于邻域正交交叉算子的人工鱼群算法

Artificial Fish Swarm Algorithm Based on Neighborhood Orthogonal Crossover Operator

将邻域正交交叉算子引入到基本人工鱼群算法中,提出了一种基于邻域正交交叉算子的人工鱼群算法。该算法采用动态调整人工鱼视野和步长的方法,较好地平衡了全局搜索能力和局部搜索能力。将人工鱼的邻域极值与该人工鱼进行正交交叉运算,产生少量的具有代表性的较优个体,而新产生的个体不仅利用了本身的有用信息,同时利用了邻域极值的最优信息,加快了算法的收敛速度,增强了算法的寻优能力。仿真结果表明,该算法具有较高的优化性能。

An artificial fish swarm algorithm was proposed based on neighborhood orthogonal crossover operator by introducing neighborhood orthogonal crossover operator into the basic artificial fish swarm algorithm. The method of dynamic adjustment of the vision and step of artificial fish to improve the abilities of searching the global and local extremum has been adopted by the algorithm. It made orthogonal crossover operation between the local extremum of artificial fish swarm and the artificial fish swarm itself to produce a few representative optimal individuals which utilized not only its own useful information but also the optimal information of local extremum to improve the fast convergence and the abilities of searching the global extremum. The test of benchmark functions showed that the algorithm improved the performance effectively.