The problem of hub construction with considering the uncertainty of hub construction cost and freight flow was discussed in this paper. A mixed integer linear programming model based on life-cycle cost theory was built to minimize the total cost for Less-than-TruckLoad (LTL) logistical hub-and-spoke network, and uncertainty decision making method based on the improved minimax regret value was proposed. Through numerical examples, the effect of investment period, coefficient of discount between hubs and uncertain hub construction cost on network design were analyzed. The experimental results show that operating cost obtained by the improved uncertainty decision making method is reduced by an average of 2.17% compared with other five scenes, which indicates that this method can decrease the total operation cost of hub-and-spoke network.

In order to solve the large-scale integral dynamic scheduling model of continuous berths and quay cranes problem, a method based on rolling-horizon strategy was proposed. A multi-objective optimization model was established under the minimization of total penalty costs of deviation to preferred berthing positions, berthing delays and departure delays. Then the scheduling process was divided into a series of continual scheduling intervals according to the dynamic arrival sequences. Meanwhile, the movement strategy of windows and parameter renew strategy were designed. The input parameters of the model in next window were renewed according to the optimal results of each window. The model for each interval was solved by choosing appropriate rolling window and freezing the quantity of vessels. The holistic optimal solution was obtained by rolling and combining the results of each window. Finally, a case study indicated that the rolling schedule can solve large-scale scheduling problems. The efficiency of the proposed approach relates to the size of rolling window, frozen ship quantity and rolling frequency.