<p>Dual-access deep-lane storage and retrieval (S/R) systems are advanced warehousing solutions that allow access to storage lanes from both ends. By adopting homogeneous assignment strategies that restrict each lane to a single item at a time, these systems enhance space efficiency and operational flexibility by reducing travel distances and relocation activities. However, their design poses significant challenges for modern logistics companies, as multiple interrelated factors affect system performance. This study proposes a multiperiod optimization model for the storage assignment of homogeneous dual-access deep-lane S/R systems. The model incorporates item homogeneity and dynamic lane depth, enabling flexible lane partitioning over time while preventing blocking and relocations. The objective is to maximize space efficiency by minimizing the nominal storage capacity required to accommodate all S/R transactions. The model is validated on a real industrial case study against a benchmark single-access storage system. In addition, a multi-scenario analysis is conducted on a multi-aisle shuttle-based S/R system to evaluate the impact of item homogeneity and lane depth. Results demonstrate the effectiveness of the proposed model as a strategic decision-support tool for the design of homogeneous dual-access deep-lane S/R systems, highlighting its industrial applicability in real-world contexts.</p>