The non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ) was applied to the multi-objective optimization of cryogenic tank ground pressurization system. Pareto solution set is sought out through Co-simulation of AMESim and Isight. Designers can choose the ideal result from Pareto solution set according to their engineering experience. The new method for the parameter designing of cryogenic tank ground pressurization system was proposed.%将带精英策略的非支配性排序遗传算法NSGA-Ⅱ(Non-dominated sorting genetic algorithm-Ⅱ)应用于运载火箭低温贮箱地面增压系统参数多目标优化问题中,采用软件AMESim和Isight实现联合仿真优化,寻优出非劣解集(Pareto解集).设计人员可依据工程经验,从Pareto解集中选出满意解.该方法为低温贮箱地面增压系统参数设计提供一种新思路.
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