Delivery Truck Arrival Scheduling Optimization Based On Estimated Traffic At Continer Terminal Gate

Under the trend of large-scale container ships,the loading capacity of container ships is generally increased,and the efficiency and capacity of container terminals in the export container terminal are facing great challenges.At present,most container terminals in China still take truck as the main mode of collection and distribution.The random arrival and centralized arrival of trucks lead to serious traffic congestion during peak hours.The truck has been idling while waiting in line,and the exhaust gas discharged during this period has also caused serious environmental pollution.Therefore,it is urgent to optimize the export containers delivery process of container terminal.In this paper,truck arrival forecast,vessel dependent time window optimization for export containers delivery considering the capacity limitation of yard,and collaborative optimization of vessel dependent time window for export containers delivery and crane scheduling.The following innovative achievements have been achieved:(1)To address the inadequacies associated with present parametric density estimations for containers' delivery and pick up time distributions,we developed a new probabilistic model based on non-parametric kernel density estimation.This proposed non-parametric estimation has better accuracy,stability and applicability than any conventional parametric distribution for containers'delivery and pick up time distributions.The curve of kernel density estimation can more accurately reflect the overall distribution pattern of containers' delivery and pick up time.It can provide more accurate traffic volume and task volume prediction for the infrastructure planning of container terminal,road traffic management,allocation and scheduling of terminal resources.(2)To cope with the congestion problem in container terminal gate and yard caused by irregular arrival of trucks,a nonlinear integer programming model was developed for the optimization of vessel dependent collection time window for export containers delivery.The minimum total idling cost of trucks at the container tennianl was taken as the objective.A two-level queuing network was used to describe the queuing process of trucks in tenninal gate and yard.This model considering both the limit of yard storage capacity and the queue length at each block,so that the model is more consistent with the reality.Then,the hybrid genetic algorithm based on simulated annealing was designed to solve the model.Numerical experiments based on the data of Dalian container terminal were given to verify the effectiveness of the proposed model and algorithm.Calculation result shows that the optimization model for vessel dependent time windows for export containers delivery can not only effectively improve the efficiency of export containers collection,dramatically reduce the idling cost of trucks,but also effectively controlled yard congestion.It can provide decision-making basis for the organization of container terminal operations.(3)The randomness of truck arrivals often leads to many problems,such as workload imbalance of cranes among different period,shortage of cranes and terminal congestion during the peak arrival period.In order to further improve the efficiency of container terminal collection operation,on the basis of vessel dependent time window optimization model considering the capacity limitation of yard,a two-stage optimization model integrates vessel dependent time windows for export containers delivery and crane deployment was developed.The number of servers(number of crane)in the yard queuing model was adjusted over time according to the scheduling scheme of cranes.A parallel genetic algorithm based on simulated annealing was designed to solve the two-stage optimization model established in this paper.Numerical experiments based on the data of Dalian container terminal were given to verify the effectiveness of the proposed model and algorithm.Calculation result shows that the model constructed in this paper can not only dramatically reduce the idling cost of trucks,but also effectively improve the utilization of RTGC and avoid waste of resources.The research results not only enrich and expand the research field of truck arrival management,but also provide a new method for the scheduling optimization of limited resources of container terminals,and also provide a reference for container terminal companies to organize container terminal operations.