Robust Storage Assignment in Unit-Load Warehouses
针对多周期中供应和需求不确定的单元载荷仓库，提出一种鲁棒优化模型，通过线性决策规则得到存储和检索策略，在需求分布不精确时仍能接近完美信息下的期望成本，优于现有启发式方法。
Assigning products to and retrieving them from proper storage locations are crucial decisions in minimizing the operating cost of a unit-load warehouse. The problem becomes intractable when the warehouse faces variable supply and uncertain demand in a multiperiod setting. We assume a factor-based demand model in which demand for each product in each period is affinely dependent on some uncertain factors. The distributions of these factors are only partially characterized. We introduce a robust optimization model that minimizes the worst-case expected total travel in the warehouse with distributional ambiguity of demand. Under a linear decision rule, we obtain a storage and retrieval policy by solving a moderate-size linear optimization problem. Surprisingly, despite imprecise specification of demand distributions, our computational studies suggest that the linear policy achieves close to the expected value given perfect information and significantly outperforms existing heuristics in the literature. This paper was accepted by Gérard P. Cachon, optimization.