Research on Integrated Scheduling Optimization of Double-trolley Quay Crane and AGV in Automated Terminal

Abstract

With the upsizing of ships, the operating efficiency of automated container terminals is becoming increasingly important. Based on the operation mode of loading and unloading synchronization, we first established an integrated scheduling optimization model of Double-trolley Quay Crane (QC) and AGV. Secondly, we designed a genetic algorithm embedded in tabu search to improve its local optimization ability. Finally, we conduct an empirical analysis. In the same case size, compared with the traditional genetic algorithm, the genetic algorithm embedded in tabu search has shorter model solving time and lower model optimal solution fitness. The maximum difference of the model solving time and the optimal solution fitness value can reach 165.113% and 7.71%, respectively. The results verify the rationality of the model and the effectiveness of the algorithm.