A Research For External Truck Deliver And Pickup Containers Scheduling Based On Truck Appointment System

With the rapid development of international trade,maritime trade between countries has become more frequent,which has promoted the rapid development of the port container transportation industry.Greater demands are being placed on the efficiency of container terminals due to the rapid growth of container throughput capacity.A large number of external trucks are concentrated at the port gates during the peak time.On the one hand,it reduces the overall operational efficiency of the port area.On the other hand,the turnover efficiency of external trucks has been reduced because of the long waiting time and low operational efficiency.The proposal of the truck appointment system has effectively relieved the problem of congestion at the port gates,but external truck scheduling is the key to the container collecting and distributing operations of the container terminal.Appropriate truck scheduling can improve the efficiency of collecting and distributing port system and reduce the truck operating cost.In this paper,we concentrate on the optimization of the external truck scheduling.Firstly,through the analyzation of the container terminal collecting and distributing process,the various work links of the external truck outside container terminal,the truck appointment system and the influence.Based on the research foundation above,this paper determines the research problem as the Multi-Port and Multi-Yard Truck dispatching problem.Taking the total operating cost of the truck fleet as the optimization goal,considering the soft time window of appointment and overtime penalty mechanism.This paper build a dispatching modal for the external tucks based on truck appointment system.Combining with the complex characteristics of the problem studied in this article,the FDT-Q algorithm(Fuzzy Double-table Q Algorithm)for truck scheduling problem based on truck appointment system is designed.We use improved ε – greedy strategy to improve the convergence efficiency of the algorithm.Considering state converging insufficient problem,a fuzzy-state-based action selection strategy is proposed,which improves the learning accuracy of the algorithm.At the same time,considering the different operating conditions between the terminal and the yard outside the port,a double action group is designed and double-Q-table is used for algorithm learning.The Q value is updated by a table-crossed update method.Finally,Discrete Event System is used to advance the simulation model to provide reference for subsequent research.Finally,experiments are designed to verify the performance of the algorithm.The results show that: 1)The F-DT-Q algorithm has good optimization performance.In the variable cost part,the optimization rate is about 48%;the overall cost optimization rate is about 11%.2)In terms of algorithm performance,the fuzzy-state-based action selection strategy can effectively shorten the number of iterations required to reach the convergence goal.The average convergence optimization time is about 19%,and as the state space increases,the convergence optimization time will continue to shorten.3)The F-DT-Q algorithm has a good dynamic scheduling ability.Considering uncertain factors such as road congestion and port operation time,compared with the original optimized sequence,F-DT-Q has a stronger self-adjusting ability.The variable cost optimization rate is about 13%.