Optimization of Container Train Service Route Based on Sea-Rail Intermodal Transportation

Since uncertain factors are affecting the operation of container trains in the process of sea-rail intermodaltransportation.Combined with the customers’ demand for a fixed time window , the uncertain planning interval is introduced to represent the range of time in container loading and unloading at each customer node.Meanwhile,the demand time window with timeliness requirements is set as a soft constraint. The penalty function is integrated into theobjective function of the transportation cost as a penalty term. A reasonable penalty coefficient is selected to constructa multi-objective optimization model of the train service path combined with the low transportation cost and less transportation time. For uncertain variables,the chance-constrained programming transformation model is used to obtain amulti-objective path optimization model considering fuzzy time. Then, the multi-objective problem is transformed intoa single objective problem by weighted summation, and the artificial bee colony algorithm is designed to solve the constructed model.The results of sea-rail intermodal transportation in Yantian Port show that:① The transportation timeis reduced by 88% in the constraint of hard time windows, but the cost is increased by 97%,fully showing the advantage of soft time windows.② When only the transportation cost is considered,the transportation time increases by5.3%. When only the transportation time is considered , the transportation cost increases by 67.8%.These experimental results confirm that the proposed model reduces the transportation cost and meets the needs of different transportation timeliness of different customers.