Abstract
Due to increasing in logistics speed, the efficiency requirements of warehousing are getting higher. Therefore, a storage location assignment model with the main goal of reducing the time traveling between the I/O point and the slot, decreasing the distance between correlation of items and ensuring the stability of shelves is proposed for the optimization of storage location in automated warehouses. To solve the model better, it is necessary to change the disadvantage of traditional genetic algorithm (GA) which is weak local search ability, thus adding an inversion operation to solve this problem. Two kinds of algorithms were used to simulate the experiment with the experimental data. After comparing the experimental results, the effectiveness of the improved GA was verified and the operational efficiency and shelf stability were increased.
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