论文标题
通过题材重新制定，基于设定的不确定多物理问题的强大优化
Set-based Robust Optimization of Uncertain Multiobjective Problems via Epigraphical Reformulations
论文作者
论文摘要
在本文中，我们研究了一种在不确定性下找到多物体优化问题的强大解决方案的方法。我们遵循基于设定的MINMAX方法来处理不确定性，这导致了严格的上层类型的关系，导致一定的设置优化问题。在某些假设下，我们介绍了使用严格的较低类型集关系的重新制定，而无需牺牲图像集的紧凑型属性。这允许应用矢量化结果以将这些设定优化问题的最佳解决方案表征为多目标优化问题的最佳解决方案。我们最终遇到了多物原理半无限问题，然后可以通过文献中的经典技术来研究这些问题。
In this paper, we study a method for finding robust solutions to multiobjective optimization problems under uncertainty. We follow the set-based minmax approach for handling the uncertainties which leads to a certain set optimization problem with the strict upper type set relation. We introduce, under some assumptions, a reformulation using instead the strict lower type set relation without sacrificing the compactness property of the image sets. This allows to apply vectorization results to characterize the optimal solutions of these set optimization problems as optimal solutions of a multiobjective optimization problem. We end up with multiobjective semi-infinite problems which can then be studied with classical techniques from the literature.
