Research on intelligent picking routing optimization based on link transmission model

This paper presents a picking box route optimization model based on the link transmission model (LTM) to address the local optimization challenges of individual picking boxes within existing warehouse transportation route optimization algorithms. The proposed model not only simulates issues such as queuing overflow and picking box detention on the transportation line but also incorporates a first-in, first-out (FIFO) strategy for picking box selection. The model's objective is to optimize the overall network traffic of the transportation line. To achieve this, the LTM is employed to simulate the backflow phenomenon of picking boxes when the conveyor line experiences blockages. Additionally, the model accounts for picking box detention and the FIFO constraint. A variable construction method based on the link is used to circumvent the enumeration of path variables. The model is formulated as a non-convex mixed-integer programming problem, which is solved using the branch and bound algorithm to determine the optimal path for each picking box on the conveyor line. This approach aims to optimize the overall network performance of the conveyor line, alleviating congestion and enhancing the picking efficiency of the system.