Collaborative Optimization Of Truck Appointment And Yard Crane Deployment In Container Terminal

The increasingly frequent trade exchanges around the world have led to the sustained and rapid growth in the business volume of container terminals.Under such circumstances,the uncertainty of the arrival time of the trucks has caused the imbalance of supply and demand of terminal resources frequently:When the supply exceeds the demand,it will cause waste of the terminal resources;And when the demand exceeds the supply,it may lead to the traffic congestion of the surrounding environment of the terminals,increase the fuel consumption and exhaust emissions of the trucks,and waste the time,money and opportunity of the truck drivers.The truck appointment system can greatly alleviate the congestion problem of the terminals by reasonably allocating the arrival time of the trucks.It can make full use of the machinery and human resources of the terminals,ease the traffic pressure and reduce environmental pollution.Therefore,it has been widely used in the current industrial environment.The truck appointment system involves many links in the terminal operation,and these links are closely related and will affect each other.In addition to the queuing the trucks,yard operation is also an important part of the appointment system.Reasonable and efficient yard crane deployment can improve the container turnover capacity of the terminals,and improve the utilization rate of the yard crane.So the research on collaborative optimization of truck appointment and yard crane deployment has rich theoretical and practical significance.Based on the new appointment mode of information exchange between the truck companies and terminals,this paper considers the collaborative optimization of truck appointment and yard crane deployment,and the optimization is to minimum the sum of the waiting cost of the trucks,the deployment cost of the yard crane in each container area The genetic algorithm is used to optimize the collaborative optimization model,and compared it with the traditional model by experiments.The experimental results show that the collaborative optimization model can effectively reduce the waiting time of the trucks.It can reduce the yard crane waste and the utilization of while giving the optimal yard crane deployment scheme,and improve the utilization of the terminal resources.It provides an effective reference for the terminal management and control of the arrival of the trucks and the yard crane deployment.