基于改进免疫遗传算法的网络优化设计

为了解决传统方法难以实现网络规划的组合优化问题, 采用改进免疫遗传算法对网络规划进行求解, 提高了种群的多样性和遗传算法的全局寻优能力。优化模型以网络架构费用最小为优化目标, 以同媒体施工、节点有限负载、网络辐射性连通为约束条件, 通过免疫规划进行网络结构的设计。进化实例表明, 改进免疫遗传算法与传统遗传算法相比, 具有较强的自适应能力和较好的效果。

Applying Improved Immune Genetic Algorithm in the Optimization Design of Network

Traditional methods are difficult to solve combinatorial optimization problems of network planning. An improved immune genetic algorithm was adopted to solve for network planning. The diversity of population and global optimization of genetic algorithm are improved greatly. The model took minimum expenses of network architecture as optimal objective, and applying the same medium, node limited load, network radiant connectivity as constraint conditions, then designs network structure by immune planning. The evolution results turn out that in comparison with conventional genetic algorithm, the improved immune genetic algorithm has better self-adaptability and effects.