论文标题
多级优化问题的近距离鲁棒版本的复杂性
Complexity of near-optimal robust versions of multilevel optimization problems
论文作者
论文摘要
近距离的鲁棒性扩展了多级优化，而较低水平的最佳解决方案的偏差有限，这是由较高级别预期的。我们分析了近距离鲁棒多级问题的复杂性，其中通过其他对抗性决策者对近乎最佳的鲁棒性进行了建模。在一般条件下，多级问题的近乎最佳鲁棒版本与问题保持在相同的复杂性类别中，而没有近距离的鲁棒性。
Near-optimality robustness extends multilevel optimization with a limited deviation of a lower level from its optimal solution, anticipated by higher levels. We analyze the complexity of near-optimal robust multilevel problems, where near-optimal robustness is modelled through additional adversarial decision-makers. Near-optimal robust versions of multilevel problems are shown to remain in the same complexity class as the problem without near-optimality robustness under general conditions.
