Search Results (2)

In the operation of the imported container area of the container yard, the fault of the yard crane often occurs, and the fault is random and unpredictable, which greatly affects the operational efficiency of the container yard. To improve the operation efficiency of the container yard, this paper studies the rescheduling optimization problem of the multi-container area and multi-yard crane when random faults occur in container lifting operations in the container import area. Considering the different impacts of different fault conditions on the container yard operation, the fault impact judgment mechanism is established. The waiting time of external container trucks and customer satisfaction is considered for yard crane rescheduling. Yard crane rescheduling model after the fault is constructed, aiming at the minimum deviation from the original scheduling scheme. And the AEA (annealing evolution algorithm) algorithm is used to solve it. The effectiveness of magic and the specificity of the algorithm are verified by the analysis of numerical examples in different scales. The research data of Dalian Port is used to carry out experiments, and the experimental analysis of examples in different scales verifies the effectiveness of the model and the scientific nature of the algorithm. Compared with the existing scheme, this scheme is more practical, which can not only give the treatment scheme immediately when the fault occurs but also effectively improve the working efficiency of the container yard and provide a reference for the port to enhance customer satisfaction. Full article

Yard handling is an important part of port logistics and affects the overall efficiency of the container port. The yard crane scheduling is affected by various external factors. For example, the dynamic cut-off time makes the release time of yard cranes variable, and the yard crane task arrangement will change frequently, resulting in a lot of computational time. To increase the flexibility of container yard handling, a twin yard cranes scheduling model is established considering the no-crossing constraints and the dynamic cut-off time. A joint scheduling of PSO and local re-scheduling strategy (LRPSO) is put forward to deal with the problem faster and more effectively. Small-scale and large-scale experiments are simulated to verify the performance of the proposed method. Results show that the scheduling method is more efficient. Full article