多项目混批背景下复杂装备研制进度计划倒排多变量CF-GERT模型及应用

进度计划是进度管控、采购等诸多工作的基础，对项目成功发挥着重要作用。复杂装备研制是一项系统工程，技术难度大，研制过程不确定性大，常出现返工、迭代，形成工作回路。此外，多项目并行研发对资源分配、进度统筹优化带来极大挑战。本课题拟对进度目标确定情形下的复杂装备研制进度倒排问题展开研究。首先，构建多项目重要度“排序屋”模型，集成国家战略需求、客户需求、竞争对手等多维度信息对项目进行排序；进而构造描述复杂装备不确定性特点的多变量特征函数型图示评审技术（MCF_GERT），设计其矩阵式求解算法，并以此为基础，将进度计划倒排问题转化成满足质量、成本、资源等约束的机会约束规划，研究其求解算法，获得进度倒排计划；然后，开发进度计划MCF_GERT网络关键环节识别技术和进度监控点优选模型，为进度管控提供重点。最后，用航天某院多项目研发为例研制和完善本课题提出的相关模型。

The schedule planning is the basis for many tasks such as schedule management and procurement, and plays an important role in the success of the project. However, due to the technology difficulty of complex equipment development, the highly uncertain development process, and lots of loops caused by rework and iteration, and developing multiple projects in a parallel manner, it is a great challenge to resources allocation and the overall optimization of schedules. This project aims to address this situation and conduct research on the schedule inversion of the complex equipment development in the context of determinate due date. First, a multi-project importance "ranking house" model is developed, integrating the national strategic needs, customer needs, competitors and other multi-dimensional information; then a multi-variable GERT based on characteristic function is constructed, which can handle the uncertainty characteristics of complex equipment. And its matrix solution algorithm is designed. Based on this technique, the problem of scheduling inversion is transformed into a chance constrained programming that meets the constraints of quality, cost, resources, etc., and the algorithm for solving the problems is deduced, with which the schedule inversion planning is got. Next, identification technology for discerning the key link of MCF_GERT network and the monitoring point optimization model is developed, providing the key for schedule control. Finally, the proposed model will be applied to the schedule inversion of the multi-project R&D project of X Academy of Aerospace, and the related models will be further verified and validated.