论文标题
在（s，q）型策略下，非平稳随机批量大小的MILP近似值
MILP Approximations for non-stationary stochastic lot-sizing under (s,Q)-type policy
论文作者
论文摘要
本文解决了单个项目的单个单个位置位置在重新订购点 - 订单数量控制策略下的非平稳随机批量大小问题。重新订购点和订单数量是在计划视野开始时选择的。允许重新排序点随时间而变化，我们认为订单数量是一系列时间依赖的常数或固定值。这导致了政策的两个变体：（ST，QT）和（ST，Q）策略。对于这两种策略，我们提出随机动态程序（SDP）来确定最佳策略参数并引入混合整数非线性编程（MINLP）启发式方法，以利用成本函数的分段线性近似。数值实验表明，我们的解决方案方法有效地计算出广泛的问题实例的近乎最佳参数。
This paper addresses the single-item single-stocking location non-stationary stochastic lot-sizing problem under a reorder point -- order quantity control strategy. The reorder points and order quantities are chosen at the beginning of the planning horizon. The reorder points are allowed to vary with time and we consider order quantities either to be a series of time-dependent constants or a fixed value; this leads to two variants of the policy: the (st,Qt) and the (st,Q) policies, respectively. For both policies, we present stochastic dynamic programs (SDP) to determine optimal policy parameters and introduce mixed integer non-linear programming (MINLP) heuristics that leverage piecewise-linear approximations of the cost function. Numerical experiments demonstrate that our solution method efficiently computes near-optimal parameters for a broad class of problem instances.
