LSTM and Linear Programming-Based Optimization for Logistics Sorting Center Operations

This study employs an LSTM model to accurately predict future cargo volumes in logistics sorting centers, and subsequently develops a linear programming model based on these predictions to optimize staff scheduling. Experimental results demonstrate that the proposed method effectively improves sorting efficiency while reducing labor costs, offering a novel strategic approach for the operational management of logistics sorting centers.