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Postoptimality Pareto-Robustness Analysis of an Earth-Observation Satellite Mission

机译:地球观测卫星任务的最优后帕累托稳健性分析

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摘要

In this paper, a methodology for postoptimality studies to assess the robustness of the Pareto-optimal solutions computed with a multi-objective optimization algorithm is presented. The proposed Pareto-robust optimization approach is based on factorial design for sampling the design region in the neighborhood of the Pareto-optimal solutions. It allows for estimating a metric for the Pareto robustness and contributes to improving convergence of the known Pareto-front toward the true Pareto front Further, sensitivity analysis of the performance and response surfaces in the neighborhood of the optimal solutions are computed without additional computational cost The proposed approach is applied to two validation test cases and to the design of a satellite Earth-observation mission for disaster monitoring. The results show that the Pareto-robust optimization approach can correctly detect Pareto-robust solutions on the Pareto front, and that it provides additional Pareto-optimal solutions at the same time, eventually improving the original known Pareto front In the case of the Earth-observation mission, the study demonstrates the possibility to enable and promote tradeoffs among the engineering team members to obtain an effective decision-making process.
机译:本文提出了一种用于后最优性研究的方法,以评估用多目标优化算法计算的帕累托最优解的鲁棒性。提出的帕累托鲁棒优化方法基于析因设计,用于对帕累托最优解附近的设计区域进行采样。它可以估计帕累托鲁棒性的度量标准,并有助于改善已知帕累托前锋向真实帕累托前锋的收敛性。此外,无需优化计算即可计算出最优解附近性能和响应面的灵敏度分析。所提出的方法适用于两个验证测试用例以及用于灾难监测的卫星地球观测任务的设计。结果表明,帕累托鲁棒优化方法可以正确地检测帕累托前沿的帕累托鲁棒解,并同时提供其他帕累托最优解,从而最终改善了原始已知的帕累托前沿。观察任务,该研究证明了在工程团队成员之间实现和促进折衷以获得有效决策过程的可能性。

著录项

  • 来源
    《Journal of Spacecraft and Rockets》 |2013年第4期|884-895|共12页
  • 作者

    G. Ridolfi; E. Mooij; S. Corpino;

  • 作者单位

    Politecnico di Torino, 10129 Torino, Italy;

    Delft University of Technology, 2629 HS Delft, The Netherlands;

    Politecnico di Torino, 10129 Torino, Italy;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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