An Iterative Re-Optimization Framework for the Dynamic Scheduling of Crossover Yard Cranes with Uncertain Delivery Sequences

In yard-crane scheduling problems, as loading operations take priority over unloading, the delivery sequence of unloading from quaysides to yard is uncertain. The changes may make crane more difficult. As a result, schedules developed statically become suboptimal or even infeasible. this paper, we propose dynamic problem considering uncertain sequences. A mixed-integer linear program assign tasks cranes and minimize makespan operations. We an iterative solution framework in which are re-optimized whenever change revealed. genetic algorithm proposed solve problem, greedy designed re-optimize update solution. To updated effect soon possible, regarding batch-based task assignment, period divided into several batches. case, instant requests arising added corresponding batch together with batch. addition, relaxation model formulated derive lower bound for demonstrating performance algorithm. Experimental results show that average gap between does not exceed 5%. insertion can time. Therefore, re-optimization feasible has advantages (necessity) assignment.