Improving the Integer L-Shaped Method
针对两阶段随机整数规划中的整数L形方法，提出两种改进策略：交替求解线性与混合整数子问题以避免耗时精确评估，以及通过割生成线性规划利用历史解信息生成最优性割，计算实验验证了效果。
We consider the integer L-shaped method for two-stage stochastic integer programs. To improve the performance of the algorithm, we present and combine two strategies. First, to avoid time-consuming exact evaluations of the second-stage cost function, we propose a simple modification that alternates between linear and mixed-integer subproblems. Next, to better approximate the shape of the second-stage cost function, we present a general framework to generate optimality cuts via a cut-generating linear program that considers information from all solutions found up to any given stage of the method. To address the impact of the proposed approaches, we report computational results on two classes of stochastic integer problems.