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Research on the Prediction of Quay Crane Resource Hour based on Ensemble Learning
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作者 Gaoshen Wang Yi Ding 《Journal of Management Science & Engineering Research》 2020年第2期31-38,共8页
In Container terminals,a quay crane’s resource hour is affected by various complex nonlinear factors,and it is not easy to make a forecast quickly and accurately.Most ports adopt the empirical estimation method at pr... In Container terminals,a quay crane’s resource hour is affected by various complex nonlinear factors,and it is not easy to make a forecast quickly and accurately.Most ports adopt the empirical estimation method at present,and most of the studies assumed that accurate quay crane’s resource hour could be obtained in advance.Through the ensemble learning(EL)method,the influence factors and correlation of quay crane’s resources hour were analyzed based on a large amount of historical data.A multi-factor ensemble learning estimation model based quay crane’s resource hour was established.Through a numerical example,it is finally found that Adaboost algorithm has the best effect of prediction,with an error of 1.5%.Through the example analysis,it comes to a conclusion:the error is 131.86%estimated by the experience method.It will lead that subsequent shipping cannot be serviced as scheduled,increasing the equipment wait time and preparation time,and generating additional cost and energy consumption.In contrast,the error based Adaboost learning estimation method is 12.72%.So Adaboost has better performance. 展开更多
关键词 The shipping industry Data driver Ensemble learning Berth allocation problem quay crane resource hour
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A two-phase tabu search approach to scheduling optimization in container terminals 被引量:1
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作者 ZENG Qing-cheng YANG Zhong-zhen 《Journal of Marine Science and Application》 2007年第2期44-50,共7页
An optimization model for scheduling of quay cranes (QCs) and yard trailers was proposed to improve the overall efficiency of container terminals. To implement this model, a two-phase tabu search algorithm was designe... An optimization model for scheduling of quay cranes (QCs) and yard trailers was proposed to improve the overall efficiency of container terminals. To implement this model, a two-phase tabu search algorithm was designed. In the QCs scheduling phase of the algorithm, a search was performed to determine a good QC unloading operation order. For each QC unloading operation order generated during the QC's scheduling phase, another search was run to obtain a good yard trailer routing for the given QC's unloading order. Using this information, the time required for the operation was estimated, then the time of return to availability of the units was fed back to the QC scheduler. Numerical tests show that the two-phase Tabu Search algorithm searches the solution space efficiently, decreases the empty distance yard trailers must travel, decreases the number of trailers needed, and thereby reduces time and costs and improves the integration and reliability of container terminal operation systems. 展开更多
关键词 two-phase tabu search container terminal quay crane scheduling yard trailer routing
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AN ANT COLONY ALGORITHM FOR YARD TRUCK SCHEDULING AND YARD LOCATION ASSIGNMENT PROBLEMS WITH PRECEDENCE CONSTRAINTS 被引量:8
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作者 Zhaojie XUE Canrong ZHANG +1 位作者 Lixin MIAO Wei-Hua LIN 《Journal of Systems Science and Systems Engineering》 SCIE EI CSCD 2013年第1期21-37,共17页
This paper examines the yard truck scheduling,the yard location assignment for discharging containers,and the quay crane scheduling in container terminals.Taking into account the practical situation,we paid special at... This paper examines the yard truck scheduling,the yard location assignment for discharging containers,and the quay crane scheduling in container terminals.Taking into account the practical situation,we paid special attention to the loading and discharging precedence relationships between containers in the quay crane operations.A Mixed Integer Program(MIP) model is constructed,and a two-stage heuristic algorithm is proposed.In the first stage an Ant Colony Optimization(ACO) algorithm is employed to generate the yard location assignment for discharging containers.In the second stage,the integration of the yard truck scheduling and the quay crane scheduling is a flexible job shop problem,and an efficient greedy algorithm and a local search algorithm are proposed. Extensive numerical experiments are conducted to test the performance of the proposed algorithms. 展开更多
关键词 Container terminal yard truck scheduling yard location assignment quay crane scheduling precedence constraints ant colony optimization
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