Storage location assignment in a multi-aisle warehouse considering demand correlations
Zheng Li
Abstract
Zheng Li
Abstract
By considering both material relevancy and requirement frequency,an optimization model for the storage location assignment in the multi-aisle warehouse was established.With the model,materials with closer relationships were compelled to be stored together closely,while at the same time,materials with high requirement frequency were stored close to the I/O point.A Hybrid Genetic Algorithm(HGA) was proposed to solve the NP problem.Numerical experiments showed that this model could obtain better results than other strategies without considering requirement correlations.As the level of demand correlations increased,the improvement was even more significant.
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By considering both material relevancy and requirement frequency,an optimization model for the storage location assignment in the multi-aisle warehouse was established.With the model,materials with closer relationships were compelled to be stored together closely,while at the same time,materials with high requirement frequency were stored close to the I/O point.A Hybrid Genetic Algorithm(HGA) was proposed to solve the NP problem.Numerical experiments showed that this model could obtain better results than other strategies without considering requirement correlations.As the level of demand correlations increased,the improvement was even more significant.
Key concepts: Aisle, Warehouse, Genetic algorithm, Point (geometry), Mathematical optimization, Computer science, Material handling, Operations research