A GPU Based Parallel Genetic Algorithm for the Orientation Optimization Problem in 3D Printing
Li, Zhishuai1,2; Xiong, Gang1,3; Zhang, Xipeng1; Shen, Zhen1,4; Luo, Can1; Shang, Xiuqin1; Dong, Xisong1,4; Bian, Gui-Bin1; Wang, Xiao1,4; Wang, Fei-Yue1
2019-05-20
Conference Name2019 International Conference on Robotics and Automation (ICRA)
Conference DateMay 20-24, 2019
Conference PlaceMontreal, Canada
Publisher2019 International Conference on Robotics and Automation (ICRA)
Abstract

The choice of model orientation is a very impor- tant issue in Additive Manufacturing (AM). In this paper, the model orientation problem is formulated as a multi-objective optimization problem, aiming at minimizing the building time, the surface quality, and the supporting area. Then we convert the problem into a single-objective optimization in the linear- weighted way. After that, the Genetic Algorithm (GA) is used to solve the optimization problem and the process of GA is parallelized and implemented on GPU. Experimental results show that when dealing with complex models in AM, compared with CPU only implementation, the GPU based GA can speed up the process by about 50 times, which helps to significantly reduce the optimization time and ensure the quality of solutions. The GPU based parallel methods we proposed can help to reduce the execution time and improve the efficiency greatly, making the processes more efficient.

KeywordOrientation Optimization Gpu Parallel Computing Genetic Algorithm Additive Manufacturing
MOST Discipline Catalogue工学::控制科学与工程
Indexed ByEI
Funding ProjectNational Natural Science Foundation of China[61533019] ; National Natural Science Foundation of China[61702519] ; National Natural Science Foundation of China[61773382] ; China Guangdong's ST Project[2017B090912001]
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/26148
Collection复杂系统管理与控制国家重点实验室_先进控制与自动化
Corresponding AuthorLi, Zhishuai
Affiliation1.the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences
2.the School of Artificial Intelligence, University of Chinese Academy of Sciences
3.the Cloud Computing Center, Chinese Academy of Sciences
4.the Qingdao Academy of Intelligent Industries
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Li, Zhishuai,Xiong, Gang,Zhang, Xipeng,et al. A GPU Based Parallel Genetic Algorithm for the Orientation Optimization Problem in 3D Printing[C]:2019 International Conference on Robotics and Automation (ICRA),2019.
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