舰基直升机群是两栖作战中立体投送、火力支援与战场侦察的核心力量，其轮转作业调度效率直接决定作战任务成败。为破解甲板资源受限下作战与保障多耦合任务协同调度难题，提升机群全流程作业的时效性与精准性，针对时间窗耦合任务的轮转调度问题开展研究。首先，系统地梳理了舰基直升机群调运、保障、出动、任务协同、回收、重组编组及再出动全流程约束条件，聚焦任务时间窗耦合特性，以最小化机群任务时间和资源配置数目为目标，构建非规则轮转作业调度模型。其次，设计融合种群分工优化策略的多目标麻雀搜索算法（MOSSA），采用4段编码架构，引入改进逆向PSGS调度生成机制，结合启发式规则实现资源与点位精准匹配；通过快速非支配排序与拥挤度距离划分种群角色，同步开展全局搜索与局部优化，实现工序与资源的高效解耦。最后，构建4个多任务协同优化场景，对比改进逆向调度与传统正向调度机制，并将MOSSA与NSGA-Ⅱ、SPEA2及MOPSO算法进行性能对比。实验结果表明：所提模型与算法可有效适配多波次出动回收协同任务需求，改进逆向调度机制能够精准匹配任务时间窗。在原始案例中，MOSSA求得的最短轮转保障时间为436 min，较NSGA-Ⅱ、SPEA2和MOPS分别缩短9.7%、12.3%和6.6%；在10次独立实验中，MOSSA的求解均值较NSGA-Ⅱ降低13.2%，标准差较MOPSO降低28.4%，并在拓展的多任务耦合场景下展现出更优的寻优精度与求解稳定性。

Shipborne helicopter groups are the core force for three-dimensional delivery， fire support and battlefield reconnaissance in amphibious operations. The efficiency of their support operation scheduling directly determines the success or failure of combat missions. To solve the problem of collaborative guarantee for multi-coupling tasks under the constraint of deck resources and improve the timeliness and accuracy of the full-process operation of the fleet， this paper conducts research on the scheduling problem of such time window coupling tasks. Firstly， sort out the entire process links and constraints of helicopter fleet transportation， support， dispatch， mission coordination， recovery， regrouping and re-dispatch. Focus on the coupling characteristics of mission time Windows， and with the goal of minimizing the mission support time and the number of resource allocations of the aircraft fleet， construct an irregular rotation support scheduling model. Secondly， a Multi-Objective Sparrow Search Algorithm （MOSSA） integrating population division optimization strategy is designed. It adopts a four-segment coding architecture and innovatively introduces an improved reverse PSGS scheduling generation mechanism. Combined with heuristic rules， it achieves precise matching of resources and points. Population roles are divided through Pareto dominance level and congestion degree， and global search and local optimization are carried out simultaneously. Achieve efficient decoupling of processes and resources. Finally， four multi-task collaborative optimization scenarios were constructed to compare and improve the reverse scheduling mechanism with the traditional forward scheduling mechanism， and performance verification was carried out with the NSGA-Ⅱ， SPEA2 and MOPSO algorithms. The results show that the proposed model and algorithm can effectively adapt to the requirements of multi-wave dispatch and recovery collaborative support. The improved reverse scheduling mechanism can accurately match the task time window. The MOSSA algorithm performs better in optimization ability and stability， providing theoretical and technical support for the support operation scheduling of amphibious carrier-based helicopter groups.