Robust Storage Assignment in Unit-Load Warehouses

Abstract

A ssigning 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.

Multi-criteria approach for products classification and their storage location assignment

“…Class-based storage policy distributes products into classes and for each class it reserves a region within the storage area in which the products are located in any way [12,20,[22][23][24]. A dedicated storage policy reserves each storage location for a specific product and no other products can be stored in that location [6,13,25]. While in randomized storage policy, the product can be allocated in any empty storage location [7].…”

“…In this sense, Ang et al [25] prefer to divide into two types of storage assignment policies, which are the dedicated storage policies and the shared storage policies. The shared storage policy is generally based on the duration-of-stay of each item and allows more flexible use of space than a dedicated storage policy [26].…”

A Robust Optimization of Capacity Allocation Policies in the Third-Party Warehouse

“…, ; represents the number of such factors used to model demand. With the assumption and theorems in Ang et al [25], we can get the equivalent form of the constraint − + ≥ 0 as follows:…”

Robust Optimization Approach to Empty Container Repositioning in Liner Shipping

“…A very desirable property is that, very often, the distributionally-robust counterpart (or a tight approximation thereof) can be efficiently computed using convex conic programs. This approach has been applied to several contexts, such as multi-period inventory control (See and Sim 2010) and warehouse management (Ang et al 2012). Using this approach, we are able to obtain a tractable approximate formulation of the empty container inventory planning problem, which is scalable both in the time dimension and the size of the shipping network.…”