Benders decomposition for internal truck renewal decision in green ports

To effectively decrease emissions and pollution emitted by equipment in container ports, many ports began to update equipment using diesel fuels to achieve the aim of green ports. This paper studies an internal truck renewal problem in container ports and proposes a two-stage stochastic programming model to optimally determine internal truck composition optimization adjustment including three renewal modes, i.e. purchasing, retrofitting, and chartering. An exact solution procedure based on Benders decomposition accelerating by Pareto-optimal cuts is developed for the proposed model. Given the problem background of Shanghai Yangshan Deep Water Port, comprehensive computational experiments are carried out to verify the effectiveness of the proposed mathematical model and the performance of the solution approach. According to the numerical experiments, some suggestions for the management of renewing internal trucks in green ports are summarized at the end of the paper.