On Quay Crane Allocation by the Hybrid Intelligent Approach GATS

This paper addresses the problem of quay crane allocation, a vital factor in container terminal operation. At first we take into consideration the diversity of the quay cranes at terminals in China and present an improved mixed-integer programming model, which considers various constraints related to the operation of QCs according to the practical background of terminals in China. In the model the objective is to minimize the total waiting service time of the container vessels at the terminal. Then we apply the hybrid intelligent approach GATS, which combines the genetic algorithm (GA) and the tabu search strategy (TS), to solve the problem. Finally we analyze the numerical result of some simulating data cases. The numerical result reveals that the hybrid intelligent approach GATS, compared with GA, gets the satisfying approximate optimal solution with much less generations, accelerates the evolution process and avoids sinking into the local optimal solution.