International Journal of Information Technology & Computer Science ( IJITCS )
In this paper, a new method for the material handling problem at marine ports is proposed in order to reduce the ship waiting time. A Q-Learning algorithm based on the number of containermovements for the material handling in the container yard terminal is used to obtain the layout of owner groups of containers, the order of movements of container, and the best removal location of each container. In the proposed method, each container has several desired positions based on its owner, so that the learning performance can be improved. In container yard terminals, containers are brought by trucks in the random order. Since each container has its own position in a vessel and it cannot be moved after loading, containers have to be loaded into the vessel in a certain order. Therefore, containers have to be rearranged from the initial arrangement into the desired arrangement before the loading. In the problem, the number of container-arrangements increases by the exponential rate with increase of total count of containers. Therefore, conventional methods have great difficulties to determine desirable movements of containers in order to reduce the run time for shipping .
: Scheduling; Container Transfer Problem; Q-Learning; Block Stacking; Reinforcement Learning .
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