Research on Multi-constrained Scheduling Model of Truck Appointment System Considering Congestion and Emission

Abstract

Container truck congestion is one of the key issues affecting the efficiency of container terminals. To alleviate the congestion of the container truck at the gate, the Truck Appointment System (TAS) has been employed at many container ports. Based on the existing TAS, a truck appointment multi-constrained scheduling model based on Mixed Integer Nonlinear Programming (MINLP) is established, which takes into account the related constraints of the appointment change cost, gate queuing cost, congestion time cost and idle emission cost in the morning and evening peak periods. Aiming at the lowest integrated operation cost of truck and port companies, a two-stage truck reservation scheduling algorithm is used to optimize the solution and obtain the best container truck scheduling scheme. The simulation results of small, medium and large scales show that multi-constrained TAS can better serve container truck and port companies and effectively reduce their comprehensive operating cost, compared with conventional TAS.