Simulation-based optimization model and metaheuristic solution of multiple crane scheduling problems

Author(s):  
H. Tamaki ◽  
S. Kitamura ◽  
H. Murao
2020 ◽  
Vol 27 (1) ◽  
Author(s):  
Gustavo Furtado da Silva ◽  
Nelson Casarotto Filho ◽  
Enzo Morosini Frazzon

Abstract Advancements in information and communication technologies are encouraging researches in shared manufacturing systems, especially on current high-competitiveness and low-resources scenarios. This paper aims to compare productive resources sharing with traditional manufacturing systems by using a simulation-based optimization model. The model is based on the One Product Integrated Manufacturing paradigm in which the efficiency optimization is pursued by designing ad-hoc virtual factories allocating the best resources available on an existing network. The proposed simulation-based optimization model is capable of identifying the best production path and plan for different distances between network members. Along with a better overall efficiency, it is also possible to argue that dedicated virtual factories ease the identification of problems and allow for improvements without negatively affecting other resources.


2021 ◽  
Vol 123 ◽  
pp. 107342
Author(s):  
Xueting Zeng ◽  
Shoujie Zhang ◽  
Tienan Li ◽  
Yong Xue ◽  
Jinyong Zhao ◽  
...  

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.


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