Optimization model of electric coal ship scheduling under considering ship storage and port congestion

被引：0
|
作者：
Chen K. [1 ]
Zhao Z.-Z. [2 ]
Wu M.-H. [2 ]
Xin X. [3 ]
Chen Z.-G. [2 ]
机构：
[1] School of Maritime Economics and Management, Dalian Maritime University, Dalian, 116026, Liaoning
[2] School of Transportation Engineering, Dalian Maritime University, Dalian, 116026, Liaoning
[3] School of Economics and Management, Tongji University, Shanghai
来源：
Jiaotong Yunshu Gongcheng Xuebao/Journal of Traffic and Transportation Engineering | 2020年 / 20卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Column generation; Electric coal transportation; Port congestion; Ship scheduling; Ship storage; Transportation planning;
D O I：
10.19818/j.cnki.1671-1637.2020.03.017
中图分类号：
学科分类号：
摘要：
In view of the actual characteristics of Chinese electric coal water transportation system, the factors of ship storage and port congestion were comprehensively considered, and a mixed integer programming optimization model was established to optimize the scheduling scheme of electric coal ships. Based on the interactive relationship among hard time window of transportation demand, waiting time of ship in unloading port and waterway-railway transportation collaboration, the minimum total cost of the transportation system was taken as objective to collaboratively optimize the freight sharing rates of waterway-railway transportation of electric coal and the task assignment, ship scheduling and storage/commissioning scheme in waterway transportation. Based on the improved column generation algorithm, a column generation algorithm was proposed to accurately solve the actual ship scheduling problem of electric coal transportation. The Gurobi was used to solve the master model generated by the column, and the dynamic programming labeling algorithm was used to solve the sub-model generated by the column. Based on the actual data of a thermal power group in Southern China, an example aimed at the proposed algorithm was analyzed. Calculation result shows that when the proposed algorithm is used to solve the middle-scale example, it takes only 73.61 s to obtain the optimal solution. Compared with the heuristic solution method based on the sequencing of traffic volume in transportation task (PHA), the solution efficiency improves by 18.1%. In a larger-scale example, the calculation time of the proposed algorithm is only 222.02 s, and the computational efficiency increases 19.1% compared with the PHA. In solving an actual scheduling problem, it is found that the proposed optimization model and algorithm can effectively shorten the waiting time of the ship at the unloading port and the active state time of the ship, and reduce the total cost of transportation by 17.13%. Therefore, they can achieve stable transportation of electric coal, improve the operating efficiency of enterprise, and reduce operating cost. 4 tabs, 4 figs, 30 refs. © 2020, Editorial Department of Journal of Traffic and Transportation Engineering. All right reserved.
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页码：178 / 191
页数：13
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