Next week the EURO conference will take place in Poznan. Amongst many interesting talks, I’d like to highlight Thanh’s presentation on “Robust Storage Loading Problems with Stacking Constraints” (in WB-47).
The accompanying paper we wrote has been published quite recently. It considers the following problem: We want to stack containers in a way that a certain weight restriction in each stack is satisfied. However, we do not know exact stack weights in advance. We follow a classic robust model, where positions cannot be changed once additional information is available, and a two-stage procedure where we only determine to which stack (or set of stacks) and item is assigned in the first stage. Then, in the second stage, we specify the precise position within the stack, once the actual weights are known.
Using an innovative description of the set of possible worst-case scenarios we need to consider, a compact formulation can be derived, which considerably outperforms a standard scenario generation approach.
This is the full abstract of the paper:
We consider storage loading problems where items with uncertain weights have to be loaded into a storage area, taking into account stacking and payload constraints. Following the robust optimization paradigm, we propose strict and adjustable optimization models for finite and interval-based uncertainties. To solve these problems, exact decomposition and heuristic solution algorithms are developed. For strict robustness, we also propose a compact formulation based on a characterization of worst-case scenarios. Computational results for randomly generated data with up to 300 items are presented showing that the robustness concepts have different potential depending on the type of data being used.