| 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
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| 2019-05-20 | |
| Conference Name | 2019 International Conference on Robotics and Automation (ICRA) |
| Pages | 2786-2792 |
| Conference Date | May 20-24, 2019 |
| Conference Place | Montreal, Canada |
| Publisher | 2019 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. |
| Keyword | Orientation Optimization Gpu Parallel Computing Genetic Algorithm Additive Manufacturing |
| MOST Discipline Catalogue | 工学::控制科学与工程 |
| Indexed By | EI |
| Funding Project | China Guangdong's ST Project[2017B090912001] ; National Natural Science Foundation of China[61773382] ; National Natural Science Foundation of China[61702519] ; National Natural Science Foundation of China[61533019] ; National 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 |
| Sub direction classification | 人工智能+制造 |
| Document Type | 会议论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/26148 |
| Collection | 复杂系统管理与控制国家重点实验室_平行智能技术与系统团队 |
| Corresponding Author | Shen, Zhen |
| Affiliation | 1.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 Affilication | Institute of Automation, Chinese Academy of Sciences |
| Corresponding Author Affilication | Institute 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),2019:2786-2792. |
| Files in This Item: | Download All | |||||
| File Name/Size | DocType | Version | Access | License | ||
| A_GPU_Based_Parallel（195KB） | 会议论文 | 开放获取 | CC BY-NC-SA | View Download | ||
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