Decision Rule Bounds for Two-Stage Stochastic Bilevel Programs
研究领导者先做二元决策、跟随者后做连续决策的两阶段随机双层规划，用现代决策规则近似构造乐观和悲观版本的上下界，转化为可高效求解的混合整数线性规划，并通过设施选址问题展示方法。
We study two-stage stochastic bilevel programs where the leader chooses a binary here-and-now decision and the follower responds with a continuous wait-and-see decision. Using modern decision rule approximations, we construct lower bounds on an optimistic version and upper bounds on a pessimistic version of the leader's problem. Both bounding problems are equivalent to explicit mixed-integer linear programs that are amenable to efficient numerical solution. The method is illustrated through a facility location problem involving sellers and customers with conflicting preferences.