Abstract
Gate and yard congestion is a typical type of container port congestion, which prevents trucks from traveling freely and has become the bottleneck that constrains the port productivity. In addition, urban traffic increases the uncertainty of the truck arrival time and additional congestion costs. More and more container terminals are adopting a truck appointment system (TAS), which tries to manage the truck arrivals evenly all day long. Extending the existing research, this work considers morning and evening peak congestion and proposes a novel approach for multi-constraint TAS intended to serve both truck companies and container terminals. A Mixed Integer Nonlinear Programming (MINLP) based multi-constraint TAS model is formulated, which explicitly considers the appointment change cost, queuing cost, and morning and evening peak congestion cost. The aim of the proposed multi-constraint TAS model is to minimize the overall operation cost. The Lingo commercial software is used to solve the exact solutions for small and medium scale problems, and a hybrid genetic algorithm and simulated annealing (HGA-SA) is proposed to obtain the solutions for large-scale problems. Experimental results indicate that the proposed TAS can not only better serve truck companies and container terminals but also more effectively reduce their overall operation cost compared with the traditional TASs.
Highlights
Over 90% of international trade is transported by ship
In order to meet these aims, we proposed a multi-constraint truck appointment system (TAS) model based on mixed integer nonlinear programming (MINLP) to determine the best appointment plan for each truck
X1 ~X6 in Table 1 indicate the unit cost of the factual time-gap is greater than the appointment, the actual time-gap is smaller than the appointment, the actual arrival time-window is later than the appointment, the actual arrival time-window is earlier than the appointment, the average waiting time at the gate, and the congestion time of the morning and evening peak periods, respectively
Summary
Over 90% of international trade is transported by ship. Container shipping is one of the dominant transportation modes. Chen et al [21] proposed a method called “ship-related time-window” to control the arrival of the trucks It only considered the congestion of the truck at the gate and the corresponding cost and did not consider the overall cost of the truck companies and the container terminals. In an attempt to fill these research gaps, this study serves as a starting point in explicitly considering both the impact of urban traffic on TAS and the overall operation costs of the truck companies and the container terminals. The aim of the study is to develop a higher-quality TAS with improved rationality and effectiveness Such a TAS can better determine the truck’s appointment time-window, lessen the impact of adjustment on the truck company’s expected appointment plans, mitigate the queue time of the truck at gates, and meet the order demand of the container terminals.
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