摘要
人工鱼群算法在算法后期容易陷入局部最优,从而降低了寻优的精度及收敛的速度。提出一种新的改进算法——DNA-鱼群算法,将DNA算法中的交叉变异操作应用到基本人工鱼群算法中,丰富了鱼群的多样性,促进人工鱼跳出局部最优,并将改进的人工鱼群算法用于解决配送中心选址分配问题。实验仿真表明,DNA-鱼群算法具有更好的寻优能力。
Since artificial fish swarm algorithm （AFSA） is easy to fall into local optimum at the latter stage, the accuracy and convergence rate of optimization are reduced. Aiming at this problem, we pro- pose an improved algorithm, called DNA-AFSA, which applies the crossover and mutation operations of the DNA algorithm to the basic AFSA. The proposed algorithm can enrich the diversity of fish stocks, thus helping the artificial fish escape from local optima. The DNA-AFSA is applied to solve the location allocation problem of distribution centers and the simulation results show that the DNA-AFSA has bet- ter optimization capability.
出处
《计算机工程与科学》
CSCD
北大核心
2016年第5期938-945,共8页
Computer Engineering & Science
