复杂装备再制造是制造的有益补充，能够显著缩短生产周期、有效节约生产成本与资源，已成为世界各国的战略选择。再制造生产进度协同优化方案制订是复杂装备再制造的首要关键问题。本项目设计复杂装备再制造生产进度协同多层次灰色GERT网络框架(MLG-GERT)；构建双情境逐级迭代辨识模型识别单项目复杂装备再制造MLG-GERT网络的关键进度链，确定最佳生产缓冲；基于瓶颈资源冲突消解研究多项目复杂装备再制造MLG-GERT网络的关键进度链协同优化问题，构造多级两层次递阶决策模型并设计主、从结构多种群蚁群算法求解关键进度链协同优化计划，设定多项目最佳生产缓冲；运用关键进度链动态趋势图实现生产进度协同MLG-GERT网络实时进度监测与预警，进而研究面向突发需求的生产进度协同计划动态调整与优化重排问题；最后以航空发动机再制造生产进度协同为例，验证模型与算法有效性，为我国复杂装备再制造计划管理提供技术方法支持。

Complex equipment remanufacturing is currently being implemented to support manufacturing, which has become a strategic choice for countries all over the world. The most important issue of complex equipment remanufacturing is to make an optimization production schedule coordination plan. A multi-layer grey GERT network model for production schedule coordination is innovatively proposed. Critical schedule chain of a multi-layer grey GERT network for one project is idendified based on a successive substitution identification model, which is with a dual identification situation. With its help, optimized production buffers are determined. On basis of it, critical scheduling chain coordination plan of multi-layer grey GERT networks for multi-project is investigated based on conflict resolution of bottleneck resource. A multi-stage decision model with two-level hierarchical structure is constructed and an ant system algorithm with master-slave structure is proposed for making an optimized production schedule coordination plan. A schedule monitoring and warning mechanism for the MLG-GERT network of complex equipment remanufacturing is established by analyzing a trend graph of critical schedule chain. A dynamic rescheduling model for obtaining production schedule coordination plan is then put forward for different emergency situations. Finally, production schedule coordination of China's aero engine remanufacturing is selected as a case, in which the models and its solution algorithm are examined and modified so as to ensure that research results are valuable for providing a technical support for complex equipment remanufacturing.