在光传输网络中经常会涉及必经网络节点问题, 即在选定了源端和宿端之后, 还指定了必须通过的局端站点, 要求建立一条最短通道的业务需求。传统的优化算法无法直接找到这样的路径。文章提出一种基于改进遗传算法的必经网络节点算法, 该算法由必经点生成随机生成树, 在随机生成树中选择必经节点间的两两子路, 并引入子路的选择概率, 借助聚类算法动态调整交叉的自适应机制提高搜索效率, 从而改进遗传算法以解决必经网络节点问题。最终, 经过论证及仿真表明采用该算法可以满足应用。

The optical transmission network is often involved in the problems of network nodes. After selecting the source and sink, the network should also designate the central site, which will establish a shortest path for business requirement. In this paper, we propose a new algorithm based on improved genetic algorithm. The algorithm generates a random tree based on the nodes. In the random spanning tree, we choose two nodes among the selected nodes. The sub-path of the node and the selection probability of the sub-path are used to dynamically adjust the crossover and mutation of the adaptive mechanism to improve the search efficiency. Therefore, the genetic algorithm is improved which can be applied to solve the necessary network node problem. Finally, the simulation results show that the proposed algorithm can meet the application.