Abstract
Due to the unprecedentedly increasing demands of waterway transportation on the Yangtze River during the latest years, traffic congestion at the Three Gorges Dam (TGD) has becoming a serious problem. In busiest seasons, a vessel may need to wait up to 3 days for passing the TGD via the ship lift or the five-stage ship lock. In order to improve the navigation efficiency and the utilization of passing facilities, a co-scheduling problem of ship lift and ship lock at the TGD is modeled in this paper. Besides, the improvement on effectiveness, safety and fairness of the navigation scheduling by introducing the ship lift is taken into account. The mathematical model proposed is, by nature, a two-stage problem, where the first-stage variables determine the assignments of passing facilities and the second-stage variables schedule the vessels. In order to solve the proposed mathematical model, a hybrid metaheuristic algorithm is used at the first stage to determine the allocation of vessels to different passing facilities and to different lockage through the maximization of facility utilization rate. The second-stage problem is then solved by CPLEX. The proposed mathematical model and algorithm are validated through a set of numerical experiments and a case study. The results show both the navigation efficiency and the utilization of passing facilities can be improved by using the proposed methods.
Highlights
The Three Gorges Dam (TGD) is the largest water conservancy and hydropower project in the world [1]
The first-stage problem maximizes the utilization of the two passing facilities, while the second-stage problem aims at minimizing the total tardiness of all vessels scheduled to pass the TGD within a given period
The model considers the improvement on effectiveness, safety and fairness of the navigation scheduling by the introduction of the ship lift
Summary
This work was supported in part by the Major Program of the National Social Foundation of China under Project 19ZDA089, in part by the Research Fund for Excellent Dissertation of China Three Gorges University under Project 2020SSPY083, and in part by the Open Access Fund at UiT The Arctic University of Norway. The work of Hao Yu was supported in part by the Research Council of Norway through the Transport 2025 Programme under Project 283084.
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