Dynamic storage assignment in homogeneous dual-access deep-lane SR systems: Dataset

This dataset supports the development, validation, and analysis of the optimization model presented in the article “Dynamic storage assignment in homogeneous dual-access deep-lane S/R systems”. It is based on a real industrial case study from the food and beverage sector and describes storage and retrieval (S/R) operations in a multi-aisle shuttle-based system. The dataset includes multiperiod storage and retrieval transactions over a 130-day planning horizon, comprising production quantities (table Q), daily demand (table D), and the list of homogeneous items (tables item_SKU, item_BATCH, item_MONTH, and item_WEEK). Structural parameters of the system are also provided, including lanes (table Z), lane depth (table P), and time horizon (table T). The initial inventory levels are also provided (table h_LAST), together with the used lanes (table er_LAST) and their partitioning (table u_LAST). The data are structured to enable replication of the computational experiments and implementation of the integer linear programming (ILP) model proposed in the paper, as well as to support sensitivity analyses on assignment strategies, lane depth, and data visibility. This dataset can serve as a benchmark for future research on deep-lane dual-access S/R systems, storage location assignment problems, and strategic warehouse design.