Abstract
Given the increasingly significant impact of an efficient product-location strategy on warehouses' performance from a service level and operational costs perspective, this paper presents a possible operations research-oriented solution to provide a tangible reduction of the overall required warehousing space, thereby translating the storage location assignment problem (SLAP) into a vertex colouring problem (VCP). Developing the topic of their previous work on the development of an effective multi-product slot-code optimization heuristic, the authors focused on finding a cost-effective way to solve the SLAP through a mathematical-optimization approach. The formulation validation on a real industrial case showed its high optimization potential, and benchmarking simulations displayed performances significantly close to the best theoretical case. Indeed, the optimized value results were definitively close to the SLAP lower bound calculated assuming a randomized storage policy which, distinct from the developed solution, must inevitably be supported by warehouse management system software. On the contrary, the proposed methodology relies upon a dedicated storage policy, which is easily implementable by companies of all sizes without the need for investing in expensive IT tools.
Highlights
According to the literature, 23% of logistics costs in the US, and 39% in Europe, are embodied by warehouse activities [1, 2]
According to what has been agreed upon in the literature in terms of proper methodologies to improve the effectiveness of the occupation of spaces and the reduction of material handling times, the dedicated storage policy – according to which each product is assigned to its own storage location – and the randomized policy – concerning a dynamic, rather than fixed, allocation of SKUs – have been the two main strategies [30, 31, 32, 33]
To the best knowledge of the authors, the absence of any detected connection between the vertex colouring problem (VCP) and the storage location assignment problem (SLAP) in the literature would lead to the belief that no one has yet tried to develop a procedure to find an efficient and cost effective solution for the warehouse management problem making use of VCPsolving methodologies, even considering the huge number of contributions that have been developed in recent years regarding this topic [76, 77, 78, 79, 80, 81, 82, 83]
Summary
23% of logistics costs in the US, and 39% in Europe, are embodied by warehouse activities [1, 2]. According to what has been agreed upon in the literature in terms of proper methodologies to improve the effectiveness of the occupation of spaces and the reduction of material handling times, the dedicated storage policy – according to which each product is assigned to its own storage location (slot) – and the randomized policy – concerning a dynamic, rather than fixed, allocation of SKUs (stock keeping units) – have been the two main strategies [30, 31, 32, 33]. The aim of this paper is to develop and present a multiproduct-allocation model based on a dedicated storage policy that is able to grant high performances in terms of the minimization of storage space and material handling times – as reachable through a randomized storage policy – while preserving the ease of product tracing guaranteed by the permanent product-slot allocation typical of a dedicated storage policy
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