摘要
为了研究多目标多学科弹道优化设计,提出了一种基于NSGA-II算法的并发多目标协作优化MDO方法MOPCO(Multi-Objective Pareto Collaboration Optimization,简称MOPCO)。利用系统优化器和学科级优化器的并发性来分解多目标MDO优化问题,解决组织复杂性问题;利用自适应响应面技术来解决计算复杂性问题;利用NSGA-II算法来搜索Pareto前沿。标准算例测试表明该算法是可行的。最后将其用于静态/动态混合优化的多目标多学科再入弹道设计,获得了合理的Pareto前沿。
A Multi-Objective Pareto Collaboration Optimization algorithm （MOPCO） is investigated to solve multi-objective multi-disciplinary trajectory design. Through the concurrency of system level optimizer and subsystem lever optimizer with response surface technology, the multi-objective multi-disciplinary optimization （MDO） problem is decomposed. And then the NSGA- II algorithm is used to search the Pareto front. The normal test case indicates the feasibility of MOPCO. Finally MOPCO is applied to the fixed static/dynamic reentry trajectory design and search the rational Pareto front successfully.
出处
《宇航学报》
EI
CAS
CSCD
北大核心
2008年第4期1210-1215,共6页
Journal of Astronautics
基金
国家863计划项目(2006AA0978)
教育部博士点基金项目
中国博士后基金项目(20070411130)
关键词
多目标优化
多学科设计优化
再入弹道
Multi-objective optimization
Multi-disciplinary optimization
Reentry trajectory
