无人机集群物资配送保障路径优化问题研究

Research of UAV Swarms Material Distribution Routing Optimization

论文以未来战场“精确保障、智能保障、灵巧保障”需求为牵引,以提升战场“最后一公里”物资保障时效为研究目标,针对战场这一特殊地域及保障环境,通过在人工蜂群算法基础上引入模拟退火算法与K-Means聚类选择算法,构建混合算法,开展无人机集群物资配送保障路径优化问题研究。实验表明,混合算法有效改善了人工蜂群算法的缺陷,在进行无人机集群配送保障路径优化时,寻优精度和有效性有明显改善,为未来智能化战争物资配送保障提供了一定的决策参考。

This paper focuses on the needs of"precise,smart and dexterous support"in the future battlefield,aims at improv-ing the effectiveness of material support"in the last mile of battlefield",and takes into consideration the special area of the battle-field and supporting environment,the simulated annealing algorithm and K-Means clustering selection algorithm are introduced on the basis of artificial bee colony algorithm,an improved artificial bee colony algorithm is proposed for UAV swarms material distribu-tion routing optimization.Experimental results show that the proposed algorithm improves the defects of artificial bee colony algo-rithm effectively,the optimization accuracy and effectiveness have been significantly improved,which provides certain deci-sion-making reference for material distribution support in the future intelligent war.