中文摘要：

针对航天器最优交会问题,基于C-W模型建立一种燃料时间混合指标,并提出一种改进和声搜索（AHS）算法进行求解.在AHS算法中,提出一种全局均匀学习操作,利用了当前全局最优和声的指导作用,取代了原始和声搜索算法的基音调整操作,增强全局搜索和局部搜索的平衡,并对参数PAR进行了有效的动态调整,以更好适应算法的搜索进程.利用几个最优交会实例对AHS算法的有效性进行了测试,数值结果表明AHS算法能够取得满意的结果,并且优于其他算法.

英文摘要：

A hybrid index of fuel-time on the basis of C-W equations was built for the spacecraft optimal rendezvous problem,and an amended harmony search（ AHS） algorithm was proposed to solve this problem. In the AHS algorithm,a global uniform learning operation was presented that the guidance of the current global best harmony was utilized and the pitch adjusting operation was replaced,resulting in the enhancement of the balance between the global search and local search.The PAR was dynamically adjusted to adapt the search process of algorithm. Several optimal rendezvous cases were used to test the effectiveness of AHS algorithm,and it was verified by the numerical results that correct satisfied results could be obtained with the proposed AHS algorithm,which is better than that of the other algorithms.