Integrated optimization method for coupling parametrization design of complex space system

Ming Wen, Cheng-shan Han
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Abstract

This paper investigates the problem of optimization method for coupling parametrization design of complex space system. The objective is to develop an integrated optimization framework to design complex space system. An improved collaborative optimization (ICO) strategy for complex design using hybrid optimization algorithm is proposed, which associates genetic algorithm (GA) with tabu search (TS). A multi-objective function with penalty terms for the system-level optimization and a relax factor for the subsystem optimization are adopted, which can avoid unsolvability or converging difficulty. The results demonstrate the applicability and effectiveness of the proposed design methodology.
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复杂空间系统耦合参数化设计的集成优化方法
研究了复杂空间系统耦合参数化设计的优化方法问题。目标是建立一个综合优化框架来设计复杂的空间系统。将遗传算法与禁忌搜索相结合,提出了一种基于混合优化算法的复杂设计协同优化策略。系统级优化采用带惩罚项的多目标函数,子系统优化采用松弛因子,避免了不可解性和收敛困难。结果证明了所提出的设计方法的适用性和有效性。
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