Under the background of a large scale of yard operations, with the aim of minimizing unbalanced workload among blocks, a collaborative optimization model for allocation of yard blocks and yard cranes was proposed by considering the influence of truck appointment information, which could allocate reasonable storage area for import containers and arrange loading and unloading yard cranes. The model was solved by CPLEX, and the experimental results of the optimization model considering truck appointment information and the traditional model without truck appointment information were compared, and the sensitivity analysis was also carried out in the aspects of truck appointment information, yards crane number, containers number and task split score. Results show that the unbalanced workload can be reduced by 20%~30% considering truck appointment information, which verifies the validity of the model and has guiding significance for the scientific management of the storage yard.