Abstract
Faced with increasing growth of container throughput and more large ships, it is necessary to improve efficiency of container terminals. This paper applies simulation and optimization technology to mimic and optimize equipment scheduling tasks in container terminals. Firstly, we propose a two-layer embedded framework, which can avoid the separation of simulation and optimization. In addition, we apply an improved agent-based multi-resolution modeling (AMRM) method to establish simulation models according to different entities of container terminals. AMRM can escape from inconsistency problem caused by MRM method. Then an improved ant colony optimization (ACO) Algorithm is introduced to optimize scheduling outputs of simulation. During the process of seeking, ants can change the size of colony adaptively and incline to select the equipment which cost less. Finally, we examine the performance of optimization of tugboat equipment scheduling in container terminals and obtain satisfactory results. It is suggested that AMRM modeling method and ACO Algorithm is well suited for application in practice
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