The multi-type liner scheduling problem in liner enterprises caused by the fluctuation of cargo demand and tide with line schedule announced in advance was studied. Firstly, the structure of near-sea transportation routes of a liner enterprise was systematically analyzed. Then, with the consideration of the real situations like large ships need to tide in and out of ports, ship renting is permitted under appropriate conditions, and the limits of a liner schedule, a nonlinear programming model of multi-type liner scheduling was built with the objective of minimizing the total transportation cost. Finally, in view of the characteristics of the model, an Improved Genetic Algorithm (IGA) embedded with gene repair was designed to solve the problem. Experimental results show that the proposed liner scheduling scheme can improve the ship utilization ratio by 25%-35% compared with the traditional experiential liner scheduling scheme, the CPU processing time of IGA is reduced by 32% on average compared with CPLEX in medium scale, and the transportation cost of IGA is reduced by 12% on average compared with ant colony algorithm in medium and large scales. All above demonstrates the validity of the proposed model and algorithm which can provide a reference for liner enterprises in liner scheduling.