Container terminal scheduling and decision-making using simulation based optimization and business intelligence

Author(s):  
Wenfeng Li ◽  
Bin Li ◽  
Yu Zhang
Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2236
Author(s):  
Hsien-Pin Hsu ◽  
Chia-Nan Wang ◽  
Hsin-Pin Fu ◽  
Thanh-Tuan Dang

The joint scheduling of quay cranes (QCs), yard cranes (YCs), and yard trucks (YTs) is critical to achieving good overall performance for a container terminal. However, there are only a few such integrated studies. Especially, those who have taken the vessel stowage plan (VSP) into consideration are very rare. The VSP is a plan assigning each container a stowage position in a vessel. It affects the QC operations directly and considerably. Neglecting this plan will cause problems when loading/unloading containers into/from a ship or even congest the YT and YC operations in the upstream. In this research, a framework of simulation-based optimization methods have been proposed firstly. Then, four kinds of heuristics/metaheuristics has been employed in this framework, such as sort-by-bay (SBB), genetic algorithm (GA), particle swarm optimization (PSO), and multiple groups particle swarm optimization (MGPSO), to deal with the yard crane scheduling problem (YCSP), yard truck scheduling problem (YTSP), and quay crane scheduling problem (QCSP) simultaneously for export containers, taking operational constraints into consideration. The objective aims to minimize makespan. Each of the simulation-based optimization methods includes three components, load-balancing heuristic, sequencing method, and simulation model. Experiments have been conducted to investigate the effectiveness of different simulation-based optimization methods. The results show that the MGPSO outperforms the others.


2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Yong Zhou ◽  
Wenyuan Wang ◽  
Xiangqun Song ◽  
Zijian Guo

The conventional approach of designing a container yard should be reexamined in the context of sustainable port development. Considering the uncertain future throughput, a simulation-based optimization framework is proposed to obtain a cost-effective and reliable design solution to the physical layout and equipment deployment strategy of the yard at a mega container terminal. In this framework, a two-stage stochastic programming model is presented aided with a simulation procedure of terminal operations. Finally, an application is given and the results show that the proposed integrated decision framework is effective and helpful for optimizing container yard design in the context of sustainable development of container terminals.


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