This thesis addresses the Multi-Period Storage Location Assignment Problem (MSLAP) through the development of a decision-support tool for optimising warehouse layouts. Applied to the case of Mepal, the tool integrates multiple slotting strategies with three improvement methods: healing, full rewarehousing, and a novel hybrid approach, combining rewarehousing and healing. Demand forecasts generated for future periods guide the assignment of items to storage locations, with the objective of minimising travel distance. Experimental evaluation using historical order data demonstrates that the hybrid method achieves substantial distance reductions compared with the current Mepal layout and with alternative strategies. Additional simulations across varied scenarios confirm the robustness and generalisability of the approach beyond the case at Mepal.