Collaborative Optimization of Rail Mounted Gantry Crane and Container Truck Based on Actual Transportation Capacity in Railway Container Terminals

To address the problem posed by limited equipment resources in railway container terminals, this study focuses on the collaborative optimization problem of rail mounted gantry crane and container truck based on the actual transportation capacity of container trucks within the mode of one-truck-two-containers. An integer programming model is formulated with the objective of minimizing truck completion times of the trucks. The model considers task allocations of containers within the one-truck-two-containers mode and incorporates safety constraints relevant to rail mounted gantry cranes. To solve the model, a genetic simulated annealing algorithm considering the distribution strategy of the rail crane is designed. Three sets of experiments with different scales are conducted to verify the feasibility and effectiveness of the proposed model and algorithm. The experimental results show that the one-truck-two-containers mode results in an average completion time reduction of 13.3% compared with the traditional collaborative operation under the one-truck-one-container mode. As the scale of examples increases, the time reduction become more significant. Furthermore, the one-truck-two-containers mode exhibits enhanced flexibility in rail mounted gantry crane operations, ensuring a more balanced workload distribution. Importantly, when the resources of container truck are limited, the one-truck-two-containers also improves the utilization rate of equipment. © 2024 Science Press. All rights reserved.