基于模糊层次分析法—粒子群算法的载人航天工程项目重要工序识别研究

Manned Space Engineering Project Based on Fuzzy Analytic Hierarchy Process-Particle Swarm Optimization Research on Identification of Important Processes

摘要:

为了更好地进行载人航天工程项目的进度管理，本文建立完整的航天项目进度风险评价体系，该体系由5个方面，21个元素，89个指标构成，涉及航天项目的设计、生产、测试等诸多过程；利用基于模糊一致矩阵的模糊层次分析法（FAHP），建立新的算法模型，将结果的一致性检验与修正过程整合为非线性规划问题，并通过粒子群算法（PSO）进行优化求解，得到满足一致性要求的权重结果，并根据结果排序识别出航天项目进度管理中的重要工序，提高事前管理的效率，保证工程项目的进度。最后以KJZ工程空间应用系统XX实验系统为例，并邀请领域专家进行打分，基于本文研究的算法进行处理，明确了该项目在进度风险控制的关键点，通过理论分析与项目实际工程进展的结果证明了该模型和方法的合理性与可行性，为载人航天项目的进度风险控制与管理提供了有效的技术支持。

Abstract:

In order to manage the progress of manned space projects better, this paper establishes a complete risk assessment system for the progress of space projects, which consists of five aspects, 21 elements and 89 indicators, involving the design, production and testing of space projects. Besides , author establishes a new algorithm model by using the Fuzzy Analytic Hierarchy Process (FAHP) based on the Fuzzy Consistency Matrix , The consistency checking and revising process of the results are integrated into a non-linear programming problem, and optimized by particle swarm optimization (PSO). The weight results satisfying the consistency requirements are obtained. According to the results, the important processes in space project schedule management are identified, so as to improve the efficiency of prior management and ensure the progress of the project. Finally, taking the space application system XX experimental system of space station engineering as an example, and inviting experts in the field to score it, based on the algorithm studied in this paper, the key points of the project's progress risk control are clarified. The rationality and feasibility of the model and method are proved by theoretical analysis and the results of actual project progress, which can be used to control the progress risk of manned space projects. It provides effective technical support with management.