The Role of Robust Optimization in Single-Leg Airline Revenue Management
提出了经典静态和动态单航段座位分配模型的鲁棒版本，考虑概率分布估计不准确的情况。模拟实验表明，鲁棒模型在平均收益几乎不变的情况下，显著降低了收益的波动性。
In this paper, we introduce robust versions of the classical static and dynamic single-leg seat allocation models. These robust models take into account the inaccurate estimates of the underlying probability distributions. As observed by simulation experiments, it turns out that for these robust versions the variability compared to their classical counterparts is considerably reduced with a negligible decrease in average revenue.