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港口集卡预约系统的配额设计与失约对策

Quota design and no-show countermeasures for port truck reservation system
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摘要 针对集卡预约系统中的预约配额方法和失约车辆再服务策略设计问题,提出一种数据驱动和数学建模相结合的决策方法。该方法通过分析码头闸口历史数据,揭示外集卡到达分布与其在港内总周转时间之间的因果关系,并以此建立一个旨在最小化外集卡港内总周转时间的优化模型。在此基础上,利用优化后的集卡预约配额方案,通过模拟考虑失约情况下车辆实际到港情况,对多种场景下的失约车辆再服务策略进行评估和决策。对Y港口的实证分析结果表明,本文的数据驱动决策方法不仅提高了模型结果的真实性和准确性,而且缩短了外集卡的港内总周转时间,并合理安排了失约车辆的再服务计划。此外,该方法具有针对具体港口的实际情况进行分析和决策的优点,能够确保集卡预约配额方案和失约再服务策略与港口实际情况相符。 Aiming at the design issues of reservation quota methods and no-show vehicle reservice strategies in truck reservation systems,the decision-making method combining data-driven and mathematical modeling was proposed.This method revealed the causal relationship between the arrival distribution of external trucks and their total turnover time in the port by analyzing historical data at the port gate,and established an optimization model aimed at minimizing the total turnover time in the external truck port.On this basis,the optimized truck reservation quota scheme was utilized to evaluate and make decisions on the reservice strategies of no-show vehicles reservice in various scenarios by using simulation to consider the actual arrival situation of vehicles in the event of no-show.The empirical analysis results of port Y indicate that the data-driven decision-making method proposed not only improves the authenticity and accuracy of the model results,but also shortens the total turnover time of outbound trucks in the port,and reasonably arranges the reservice plan of no-show vehicles.In addition,this method has the advantage of analyzing and making decisions based on the actual situation of specific ports,and can ensure that the container truck reservation quota scheme and no-show reservice strategy are consistent with the actual situation of the port.
作者 孙世超 史欣 董曜 SUN Shi-chao;SHI Xin;DONG Yao(College of Transportation Engineering,Dalian Maritime University,Dalian 116026,China)
出处 《大连海事大学学报》 CAS CSCD 北大核心 2023年第2期91-102,共12页 Journal of Dalian Maritime University
基金 国家自然科学基金资助项目(72202025) 中央高校基本科研业务费专项资金资助项目(3132022188)。
关键词 集装箱运输 集卡预约系统 预约配额设计 失约车辆再服务策略 数据驱动 计算机仿真 container transport truck appointment system appointment quota design no-show vehicles reservice strategy data-driven computer aided simulation
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