Yard Truck Scheduling and Storage Allocation in Container Terminals: Multiobjective Approach

Truck scheduling and storage allocation, as two separate subproblems in container terminal operations, have attracted some good research efforts in past decades. Pratically speaking, these two subproblems of truck scheduling and storage allocation are highly interdependent in container terminal operations. The optimal storage allocation depends highly on the yard truck schedule; meanwhile, the optimal yard truck schedule is also influenced by the storage location of containers. Therefore, instead of handling these two subproblems in a sequential way, we propose a multi-objective mixed integer programming model that integrates the two subproblems into a whole. The first objective is to minimize the total travel time of yard trucks while the second one is to minimize the total delay of containers. Pareto ranking method is applied to evaluate the objectives. Solutions on Pareto frontier can be considered as the optimal solutions, since no other solutions dominate them. Ready time of containers constrained by quay crane schedule is also considered in this model as an interface with the quay crane scheduling problem. Due to the inherent intractability of the problem, a hybrid Genetic Algorithm incorporating the storage allocation heuristic is designed to attain near optimal solutions. It shows from the computational results that the proposed solution algorithm can obtain the Pareto solution in short time. It can also be observed that proposed integrated method can greatly improve the efficiency of terminal operations compared with the benchmark model that solves the two subproblems sequentially.