Jiabin Luo and Yue Wu
automated container terminal, vehicle scheduling, container storage, container unloading
Efficient scheduling of vehicles and allocating container storage locations are important in container terminal operations. This research investigates the integration of these two problems for the unloading process in an automated container terminal. The detailed schedule for each vehicle during the unloading process and the allocated storage location for each container are determined. A mixed-integer programming (MIP) is provided. A series of experiments are carried out: existing solver for small-sized problems and a genetic algorithm (GA) for large-sized problems. The solutions from GA are compared with the optimal solutions obtained from existing optimisation solver in small-sized problems. The results show that both the model and solution methods are efficient in solving the integrated optimisation problem.
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