The retail industry is becoming increasingly competitive; as a result, companies are seeking to reduce inefficiencies in their supply chains. One way of increasing the efficiency of operations inside a warehouse is by better allocating products in the available spaces. In this paper, we propose a new heuristic approach to solving the storage location assignment problem (SLAP) considering precedence constraints, in multi-aisle, multi-product picking warehouses. A two-phase heuristic procedure is developed: the products are clustered and assigned to the available spaces. We tested the procedure in the non-perishables warehouse of a real-world Portuguese retail chain, which supplies 191 stores per day. The results show that the new assignment of products allows for an improvement of up to 15% on the distance travelled by the pickers, which implies savings of approximately 477 km per month. This problem is a special case of SLAP since we are dealing with large percentages of non-uniform products. This procedure incorporates four relevant criteria for the allocation decision: the products’ similarity, demand and weight, and the distance travelled by the picker. By using a two-phase heuristic method, this study offers companies and academics an alternative and more effective solution for SLAP than the usual methods based on the creation of density zones.

零售业竞争日趋激烈；因此，公司正在寻求减少其供应链中的低效率。提高仓库内运营效率的一种方法是在可用空间中更好地分配产品。在本文中，我们提出了一种新的启发式方法来解决多通道、多产品拣选仓库中考虑优先约束的存储位置分配问题 (SLAP)。开发了一个两阶段启发式程序：将产品聚类并分配到可用空间。我们在一家真实的葡萄牙零售连锁店的不易腐烂仓库中测试了该程序，该零售连锁店每天供应 191 家商店。结果表明，新的产品分配可以将拣货员行驶的距离提高多达 15%，这意味着每月节省大约 477 公里。这个问题是 SLAP 的一个特例，因为我们正在处理很大比例的非均匀产品。该程序包含四个相关的分配决策标准：产品的相似性、需求和重量，以及拣货员行进的距离。通过使用两阶段启发式方法，本研究为公司和学者提供了一种替代且更有效的 SLAP 解决方案，而不是基于创建密度区的通常方法。