Optimization model of terminal container truck appointment based on coordinated service of inner and outer container trucks
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摘要: 针对码头集卡集中到达引起的拥堵问题, 提出了基于内外集卡协同服务的码头集卡预约优化模型, 建立了休假式排队系统, 设计了基于遗传算法的求解方法, 并利用算例验证了模型与算法的有效性。分析结果表明: 内部集卡在堆场的计算平均等待时间为14.31 min, 实际平均等待时间为15.11 min, 外部集卡在堆场的计算平均等待时间为20.65 min, 实际平均等待时间为21.55 min, 计算值与实际值相差较小; 预约优化后外部集卡在堆场的平均等待时间由20.65 min缩短为16.85 min, 码头集卡的平均等待成本由29.3元降低为24.1元。休假式排队可有效描述码头内部集卡和外部集卡的特征。可见, 集卡预约优化模型能有效降低码头集卡的等待成本与等待时间, 建议对集卡进行管理时应优先考虑减少内部集卡的等待时间。Abstract: Aiming at the congestion problem induced by terminal container trucks arriving together, an optimization model of terminal container truck appointment based on the coordinated service of inner and outer container trucks was proposed, the vacation queuing system was built, the solving method based on genetic algorithm was designed, and the numerical experiments were provided to illustrate the validity of the model and the method.Analysis result indicates that the calculated average waiting time of inner container trucks at yard is 14.31 min and the actual average waiting time of inner container trucks at yard is 15.11 min.The calculated average waiting time of outer container trucks at yard is 20.65 min and the actual average waiting time of outer container trucks at yard is 21.55 min.The difference between the calculated values and the actual values is small.After the appointment optimization, the average waiting time of outer container trucks at yard decreases from 20.65 min to 16.85 min and the average waiting cost of terminal container trucks decreases from 29.3 yuan to 24.1 yuan.The vacation queuing model can effectively describe the service process of inner and outer terminal container trucks.Obviously, the appointment optimization model of container trucks can decrease the waiting cost and time of terminal container truck.Managing container truck should give priority to decreasing the waiting time of inner container truck.
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表 1 集卡等待成本
Table 1. Waiting costs of container trucks
表 2 集卡的总等待成本
Table 2. Total waiting costs of container trucks
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