Abstract
At present, a lot of studies on automatic terminal scheduling are aimed at the shortest operating time. An effective way to reduce the operating time is to increase the amount of operating equipment. However, people often ignore the additional costs and energy consumption caused by increasing the amount of equipment. This paper comprehensively considers the two aspects of the equipment operation time and equipment quantity matching. With the minimum total energy consumption of the operating equipment as the objective function, a cooperative scheduling model of Automated Guided Vehicles (AGVs) and dual Automated Yard Cranes (AYCs) is established. In the modelling process, we also considered the interference problem between dual Automated Yard Cranes (AYCs). In order to solve this complex model, this paper designs an improved multilayer genetic algorithm. Finally, the calculation results from CPLEX and a multilayer genetic algorithm are compared, and the effectiveness of the model and algorithm is proved by experiments. In addition, at the same time, it is proved that it is necessary to consider the interference problem of dual Automated Yard Cranes (AYCs), and the optimal quantity matching scheme for the equipment and the optimal temporary storage location is given.
Highlights
Introduction and Literature ReviewWith the deepening of economic globalization, the status of automated container terminals is becoming increasingly prominent
(1) By evaluating the performance of the algorithm for solving Automated Guided Vehicles (AGVs) and Automated Yard Cranes (AYCs) collaborative scheduling problems under different scale tasks, it is concluded that the multilayer genetic algorithm is very effective at solving complex scheduling problems
When the container’s loading and unloading tasks are determined, the collaborative scheduling optimization scheme of AGVs and AYCs can be obtained by using the multilayer genetic algorithm
Summary
With the deepening of economic globalization, the status of automated container terminals is becoming increasingly prominent. Huang and Han [11] proposed a mixed-integer programming model for the collaborative scheduling problem of dual automatic stacking cranes (AYCs) with both of the operations (storage and retrieval) on a single container block of an automated container terminals. A genetic algorithm based on job sequence coding was designed and multiple sets of practical examples were solved by using CPLEX and a genetic algorithm and by considering the interference between dual AYCs. Zhan et al [12] discussed the load scheduling problem of multiple yard cranes. Pei and Chang [24] proposed a mixed-integer programming model to minimize the total operating time and the distance between dual ARMGs on the basis of considering the coordination of the ARMGs and the capacity of the seaside handover point.
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