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

建立较为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,以便更好地进行工程项目进度管理。最后以载人航天工程X项目为例,证明该方法的合理性与可行性。

This paper establishes a relatively complete aerospace project schedule risk assessment system,which consists of 5 aspects,21 elements and 89 indicators,involving the design,production,testing and other processes of aerospace projects;using fuzzy analytic hierarchy analysis based on fuzzy consistent matrix The method(FAHP)establishes an algorithm model,integrates the consistency check and correction process of the results into a nonlinear programming problem,and optimizes the solution through particle swarm optimization(PSO)to obtain weight results that meet the consistency requirements,sorts and identifies them according to the results.Out of the important processes in the aerospace project schedule management,improve the efficiency of ex ante management,in order to better carry out project schedule management.Finally,taking the manned space engineering X project as an example,the rationality and feasibility of the method are proved.