Optimization Model for Truck Appointment in Container Terminals

摘要

Many ports are facing heavy truck congestion in the terminal, which leads to longer truck waiting time and lower operation efficiency. To alleviate congestion and decrease truck turn time in the container terminal, an optimization model for truck appointment was proposed in this paper. In the model, the appointment quota of each period was optimized subject to the constraints of adjustment quota. And a BCMP queuing network was developed to describe the queuing process of trucks in the terminal. To solve the model, a method based on Genetic Algorithm (GA) and Point wise Stationary Fluid Flow Approximation (PSFFA) was designed. GA was used to search the optimal solution and PSFFA was designed to calculate the truck waiting time. Finally, numerical experiments were provided to illustrate the validity of the model and algorithm. The results indicate that the proposed PSFFA method can estimate the queue length accurately and the model can decrease the truck turn time efficiently.