Optimization of container handling systems in automated maritime terminals: A hybrid genetic and a tabu search algorithms

In automated maritime terminals at import, containers location problem and QC-AGV-ASC planning are generally treated separately. This approach is not efficient because container location has a direct impact on the QC-AGVASC planning optimality. In this paper, we resolve the planning of QC-AGV-ASC tasks and the containers location problem in automated maritime terminals at import in one time. We propose a new bi-objective model determining the minimal storage time with the optimal storage space organization. We minimize the makespan “date of last task” and the storage space organization with a priority of minimizing the storage time. We organize the storage space by minimizing the risk of unproductive moves caused by containers location decision. We propose a hybrid genetic and a tabu search approaches to solve efficiently the problem.