Multi-Equipment Coordinated Scheduling Considering Energy Consumption in Sea-Rail Intermodal Container Terminal
With the growth of multimodal transportation and the push for green ports,improving the efficiency of sea-rail intermodal transportation and reducing energy consumption have become critical concerns for ports.This study focused on optimizing the layout of shared yards between the railway and terminal operation areas at a container terminal.The objective is to minimize operation completion time and optimize the energy consumption of Rail-Mounted Gantry(RMG)cranes and Automatic Guided Vehicles(AGV),thereby improving the utilization rate of RMGs.To achieve this,a coordinated scheduling optimization model is developed for RMGs,AG Vs,and yard cranes within a mixed loading and unloading environment.The model considered interference and task allocation among the RMGs,capacity constraints of AGV partners,and energy consumption variations during different AGV states such as loading,unloading,and waiting.In addition,a task assignment strategy that considered interference constraints is introduced for RMG operations.An improved hybrid grey wolf genetic algorithm is proposed to solve the model.This algorithm incorporated a grey wolf algorithm position update strategy to enhance the crossover method of the genetic algorithm,thereby improving the efficiency of finding optimal solutions.A reward-based evaluator is also introduced before the selection step of the genetic algorithm to enhance the local search capability of the algorithm.Experimental results indicated that considering task allocation for RMGs improved their average utilization rate by 3％-8％compared to scenarios where the RMG operating range is predetermined.Furthermore,the improved hybrid grey wolf genetic algorithm reduced energy consumption more effectively within a shorter completion time compared to adaptive chaotic and traditional genetic algorithms.In conclusion,this study provides an effective and superior solution for improving efficiency and reducing energy consumption in sea-rail intermodal transportation at container terminal.
sea-rail intermodal transportationcoordinated schedulingmixed loading and unloadingtask assignmentimproved hybrid gray wolf genetic algorithm
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