基于均值聚类的KMCPSO舰载机出库调度算法

The KMCPSO Aircraft Carrier Outbound Schedule Optimization Based On Mean Clustering

航母舰载机的出库调度效率,在很大程度上决定了整个航母的战斗力生成。通过研究K均值聚类算法的基本原理,提出基于均值聚类的KMCPSO舰载机出库调度算法。该算法针对粒子群算法在进化过程中易出现早熟和寻优结果不稳定的缺陷,通过在迭代过程对种群进行分群,以提高种群多样性,从而克服原算法的不足。基于俄罗斯“库兹涅佐夫”号航母舰载机出库任务,建立舰载机调度模型,并用KMCPSO算法进行求解。结果表明,KMCPSO算法能克服上述缺陷,模型有较好的应用价值。

The combat effectiveness of aircraft carrier is largely determined by the Outbound- Scheduling efficiency of the air-craft. After researching the basic principle of K-Means cluster Optimization,the KMCPSO Aircraft Outbound Schedule Optimization has been put forward based on it.The shortcomes of Particle Swarm Optimization have been solved in the evolutionary process of the new Optimization,such as Proning to premature,the optimization result is not stable.The population diversity has been enhanced by dividing populations in the Optimization. The Aircraft scheduling model has been established based on the outbound task of the aircraft carrier ＂admiral kuznetsov＂ in Russia. The model is solved by the K-Means Cluster Particle Swarm Optimization. The results show that the optimization can solvel the above defects and the model has good application value.