컨테이너 선박 마스터 적하계획을 위한 심층 강화학습 모형

Abstract

In the Port Logistics system, Container Stowage planning is an important issue for cost-effective efficiency improvements. At present, Planners are mainly carrying out Stowage planning by manual or semi-automatically. However, as the trend of super-large container ships continues, it is difficult to calculate an efficient Stowage plan with manpower. With the recent rapid development of artificial intelligence-related technologies, many studies have been conducted to apply enhanced learning to optimization problems. Accordingly, in this paper, we intend to develop and present a Deep Q-Learning Network model for the Master Stowage planning of Container ships.