Abstract
In this paper, we study the Quay Crane (QC) assignment for incoming vessels by introducing hard time windows into the container terminal. Given a nonlinear programming model, a set of 0-1 variables is employed to describe the starting position of the operation for each QC in a certain vessel. We also employ another set of 0-1 variables to locate the ending operation position for each QC in the same vessel. The research objective is to minimize the maximum operation time of each QC. This is a typical NP-hard problem, so a genetic algorithm is applied to the searching of the optimum solution in real-time applications. We carried out a series of experiments in order to evaluate our model. The results show that the proposed model and algorithm can signiflcantly raise the operating e‐ciency of the container terminal.
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