In this paper, we develop an approximation scheme for solving bilevel programs with equilibrium constraints, which are generally difficult to solve. Among other things, calculating the first-order derivative in such a problem requires differentiation across the hierarchy, which is computationally intensive, if not prohibitive. To bypass the hierarchy, we propose to bound such bilevel programs, equivalent to multiple-followers Stackelberg games, with two new hierarchy-free problems: a $T$-step Cournot game and a $T$-step monopoly model. Since they are standard equilibrium or optimization problems, both can be efficiently solved via first-order methods. Importantly, we show that the bounds provided by these problems -- the upper bound by the $T$-step Cournot game and the lower bound by the $T$-step monopoly model -- can be made arbitrarily tight by increasing the step parameter $T$ for a wide range of problems. We prove that a small $T$ usually suffices under appropriate conditions to reach an approximation acceptable for most practical purposes. Eventually, the analytical insights are highlighted through numerical examples.
翻译:在本文中,我们制定了一个近似方案,以解决有均衡限制的双级方案,一般很难解决。除其他外,在这样一个问题中,计算一阶衍生物需要不同层次的差别,这种差别在计算上是密集的,如果不是令人望而生畏的话。为了绕过等级,我们提议将这类双级方案,相当于多追随者Stackelberg游戏,有两个新的无等级问题:一是T$-step Cournot游戏,二是一阶垄断模式。由于它们是标准的平衡或优化问题,两者都可以通过一阶方法有效解决。 重要的是,我们表明这些问题所提供的界限 -- -- 由$T$-step Cournot游戏的上限和一阶地价垄断模式的下限 -- -- 可以通过为一系列广泛的问题增加阶梯参数$T$。我们证明,在适当的条件下,一小块T$通常足以达到最切合实际的近似值。最后,通过数字例子来突出分析洞察力。