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Irregular external truck arrivals at a marine container terminal often leads to long queues at gates and substantial greenhouse gas emissions. To relieve gate congestion and reduce carbon emissions, a new truck arrival pattern called “vessel dependent time windows (VDTWs)” is proposed. A two-phase queuing model is established to describe the queuing process of trucks at gate and yard. An optimization model is established to assign time window and appointment quota for each vessel in a marine container terminal running a terminal appointment system (TAS) with VDTWs. The objective is to minimize the total carbon dioxide emissions of trucks and rubber-tired gantry cranes (RTGCs) during idling. The storage capacity constraints of each block and maximum queue length are also taken into consideration. A hybrid genetic algorithm based on simulated annealing is developed to solve the problem. Results based on numerical experiments demonstrate that this model can substantially reduce the waiting time of trucks at gate and yard and carbon dioxide emissions of trucks and RTGCs during idling.

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