摘要
为求解无约束优化问题,将生物免疫系统中免疫行为可以保持种群多样性从而避免陷入局部最优和出现早熟收敛现象这一特性应用到标准遗传算法中,给出了一种新的基于疫苗接种的免疫遗传算法。数值试验结果表明算法对于多峰值函数有很好的优化效果。当群体迭代可能陷入局部最优时,新的算法通过适时的动态疫苗接种使个体及时跳出局部最优解,最终求得全局最优解。
To solve unconstrained optimization problems,applying the properties of diversity of the population can be maintained in the immune system to avoid falling into a local optimum and the phenomenon of premature convergence to standard genetic algorithm,a new immune genetic algorithm based on vaccination is put forward.The results of the experiments show that the new algorithm has good performance to the function which has many local optimal solutions.The advantage of this algorithm is that, When the group iterative is likely to fall into local optimum,the individuals are able to jump out of local optimal solution in time through timely dynamic vaccination and ultimately achieve the global optimal solution.
出处
《计算机工程与应用》
CSCD
北大核心
2009年第1期45-47,共3页
Computer Engineering and Applications
基金
陕西省教育厅专项基金资助项目~~
关键词
动态疫苗接种
免疫
遗传算法
dynamic vaccination
immune
genetic algorithm
