Abstract
The extensive application of emerging technologies is revolutionizing warehouse management. These technologies facilitate working with complex and powerful warehouse management models in which products do not have assigned fixed locations (random storage). Random storage allows the utilization of the available space to be optimized. In this context, and motivated by a real problem, this article presents a model that looks for the optimal allocation of goods in order to maximize the storage space availability within the restrictions of the warehouse. For the proposed model a construction method, a local search algorithm and different metaheuristics have been developed. The introduced algorithms can also be used for other purposes such as to assess when and how it is convenient to perform relocation of stored items to improve the current level of storage space availability. Computational tests performed on a set of randomly generated and real warehouse instances show the effectiveness of the proposed methods.
Published Version
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