多重不确定因素影响下的高端装备研制任务流程优化

基于设计结构矩阵对高端装备研制任务进行仿真建模,采用蒙特卡罗方法模拟研制任务执行过程,用以估算其工期、成本、失败率等参数.将研制任务仿真嵌入到多目标优化算法中,对每个个体对应的研制任务流程进行多次仿真,以仿真输出的平均工期、成本、失败率等作为适应度评价指标,基于NSGA-III构造多目标优化算法,求解其Pareto最优解集.对每个Pareto最优解对应的研制任务流程进行更多次的仿真,在此基础上对各个研制任务流程进行深入分析、评价.最后,以某无人机研制任务为例进行应用研究,并把本文的优化结果与文献中的数据进行比较,检验了本文方法的有效性和优越性.

Optimization of high-end equipment development task process influenced by multiple uncertainty factors

The simulation model of high-end equipment development task is established based on design structure matrix, and Monte Carlo method is used to simulate the execution process of the development task. The simulation outputs are used to estimate the duration, cost, failure rate and other parameters of the development task. The development task simulation is embedded into multi-objective optimization algorithm, and each individual corresponding development task process is simulated many times. The average duration, cost and failure rate of simulation outputs are used as fitness evaluation indexes. Multi-objective optimization algorithm is constructed based on non-dominated sorting genetic algorithm-Ⅲ (NSGA-Ⅲ), the Pareto optimal solution set is obtained by running optimization algorithm. More simulations for the development task process of each Pareto optimal solution are carried out, and the development task processes are deeply analyzed and evaluated. Finally, an uninhabited combat aerial vehicle development task is taken as an example to study the application, and the optimization result of this paper are compared with the data in the literature. The effectiveness and superiority of the proposed method are verified.