Iterative Replanning using Genetic Algorithms for Remarshaling in a Container Terminal

T. Park, J. Kim, and K.R. Ryu (Korea)


Automated container terminal, remarshaling, genetic algorithm, and dynamic optimization problem


Remarshaling of a stacking yard in a container terminal refers to the task of rearranging the containers to improve the efficiency of the subsequent loading operation onto a ship. This paper proposes an iterative replanning method for remarshaling by using genetic algorithms. Since the time available for the remarshaling operation is usually limited, not all the containers in the stacking yard can be remarshaled. The proposed planning method works in two steps: selecting the containers for remarshaling followed by building a remarshal schedule for the selected containers. However, a plan thus generated cannot exactly fit the reality due to some estimation errors made during planning and the uncertainty of crane operations during the execution. Considering this as a characteristic of a dynamic optimization problem, the proposed method iteratively replans by employing a genetic algorithm which can search efficiently by reusing the solutions obtained from the previous iterations. Experimental results show that the proposed method outperforms other methods which either do not replan or do not use previous solutions.

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