Design of Interconnected Warehouse and Routing Optimization by BP Genetic Neural Network Algorithm

With the continuous progress of the chemical industry, warehouse design needs to be diversified on account of the increasing complex and multitudinous perilous chemicals. In this situation, this study projects the conception of the interconnected warehouse. By taking the storage points as the quantity and the path as the variable, this study establishes a quadratic allocation model on the operations of this novel kind of warehouse. Then, an improved neural network algorithm is proposed to ascertain the optimal solution. The innovation of this study is that it releases the space resources of the classic dangerous goods warehouse and improves the operational efficiency of the dangerous goods warehouse under the premise of ensuring safety. Finally, the proposed model and algorithm is tested and verified with a data of Shanghai Lingang dangerous Material Warehouse. The empirical research demonstrates that the interconnected warehouse has ideal performance for lifting the handling efficiency on the basis of ensuring safety.