一种数据驱动的港口外集卡预约配额设计方法

A data-driven design method for appointment quota of container trucks outside ports

针对集装箱卡车预约配额优化问题,提出一种数据驱动的集装箱卡车预约配额设计方法。该方法通过分析码头闸口数据(车辆进出闸口信息),揭示车辆到达时间分布与车辆总周转时间之间的因果关系,并以此建立和求解车辆到达时间分布优化模型,实现集装箱卡车预约系统的预约配额设计。以盐田港的数据为例,对该方法的可行性进行实例分析。数据挖掘的结果表明,在每一个预约窗口内,作业类型为“提进口空箱作业”以及“一交一提作业”的外部集装箱卡车,其总周转时间与车辆到达数量呈二次函数关系;而作业类型为“交出口重箱作业”的外部集装箱卡车则表现出线性函数关系。数例分析结果表明,基于上述函数关系所构建的集装箱卡车预约配额优化方法,可以有效降低码头车辆的总周转时间以及因交通拥堵产生的温室气体排放。此外,该方法是基于实证数据分析得到的,因此具有较强的泛化性和实用性,可为各个码头优化集装箱卡车预约份额提供参考。

Aiming at the optimization of container truck reservation quota, a data-driven design method of container truck appointment quota was proposed. This method revealed the causal relationship between the distribution of vehicle arrival time and the total turnover time of vehicles by analyzing the data of the smart gate(information of vehicle entrance and exit), and then established and solved the optimization model of vehicle arrival time distribution to realize the appointment quota design of the container truck appointment system. Taking the data of Yantian port as an example, the feasibility of this method was analyzed. The results of data mining show that in each appointment window, the total turnover time of the external container trucks with the operation types of “pick imported empty containers”and “one-delivery-one-pick”is a quadratic function relationship with the number of vehicles arriving, while the external container truck with the operation type of “delivery exported full containers” shows a linear functional relationship. The examples analysis results show that the optimization method of container truck appointment quota constructed based on the above-mentioned functional relationship can effectively reduce the total turnover time of dock vehicles and the greenhouse gas emissions caused by traffic congestion. In addition, the method is based on empirical data analysis, so it has strong generalization and practicability, which can provide reference for each terminal to optimize the container truck appointment share.