Effective storage location assignment model based on a genetic simulation annealing algorithm.

Automated warehouses have become the main application equipment in logistics due to their access automation and simple operation. In order to adapt to the increasingly rapid logistics speed, it is necessary to optimise the location assignment of items in the automated warehouse. Firstly, according to the characteristics of the automated warehouse operation environment, the storage location assignment optimisation model with the shortest time of items travelling the warehouse, the minimum distance between related items and the lowest orthocentre of the shelf is proposed. Then according to the characteristics of the optimisation model and the shortcomings of the traditional genetic algorithm (GA), the defects of the GA are improved and the fusion with the simulated annealing algorithm (SA) is completed, so as to form an improved genetic simulation annealing algorithm (SAGA) for the model. Finally, the effectiveness and superiority of the improved fusion algorithm are verified by comparing the SA, the SAGA and the improved SAGA.