Publication | Open Access
Storage Location Assignment Heuristics Based on Slot Selection and Frequent Itemset Grouping for Large Distribution Centers
20
Citations
26
References
2020
Year
Cluster ComputingFacility PlanningEngineeringStorage ManagementOperations ResearchSystems EngineeringLogisticsLogistics ModelCombinatorial OptimizationFrequent ItemsetTransportation EngineeringQuantitative ManagementCapacity ManagementHeuristic ApproachesCapacity PlanningComputer EngineeringSupply Chain ManagementComputer ScienceStorage AllocationRoute ChoiceSlot SelectionLarge Distribution CentersRoute PlanningBusinessVehicle Routing ProblemFrequent Itemset Grouping
This paper considers heuristic approaches that can be used to assign stock keeping units (SKU) to individual slots in distribution center. Firstly, we propose two novel strategies, slot selection and frequent itemset grouping. The former is used to find the most suitable slot for a single SKU, while the latter is for sequencing SKUs in an appropriate order. Secondly, we develop several storage location assignment heuristics by applying the two strategies. Especially, the heuristics are designed to assign frequently ordered SKU to a slot close to I/O (input/output) point and SKUs frequently ordered together to slots close to each other. Consequently, the proposed heuristics are helpful to reduce the travel distance of order picker in distribution center. In this paper, travel distance of order picker is calculated based on a routing policy that enables order picker to move along a flexible route. For illustration, we applied the heuristics to real data collected from a large distribution center. The experiment results reveal that slot selection strategy is very helpful to reduce average travel distance of order picker, especially under greedy routing policy. Also, frequent itemset grouping strategy can provide additional reduction in average travel distance if it is applied together with slot selection strategy.
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