期刊
NEUROCOMPUTING
卷 446, 期 -, 页码 74-85出版社
ELSEVIER
DOI: 10.1016/j.neucom.2021.03.029
关键词
Multi-task scheduling; Service quality; Game theory; 3D printing; Cloud manufacturing
资金
- National Natural Science Foundation of China [61873014]
- National High-tech Research and Development Program [2015AA042101]
The proposed non-cooperative game model and two-layer nested method based on genetic algorithm improve the multi-task scheduling efficiency of distributed 3D printing services in cloud manufacturing, achieving the goal of enhancing service quality and reducing costs. The experimental results demonstrate that this method outperforms traditional scheduling methods.
To improve the multi-task scheduling competitivenesss of the distributed three-dimensional (3D) printing services with different types in cloud manufacturing, a non-cooperative game model of 3D printing services is proposed to reduce completion time, cost and to improve service quality. Moreover, the non-cooperative game consists of two kinds of sub-game to work together. Some service attributes, such as moving speed of nozzle, model dimension, 3D printing precision, 3D printing material, and pricing mode, are considered in the model. In order to obtain the expected solution, a two-layer nested method based on genetic algorithm is developed to improve scheduling efficiency. An industrial case is given to verify the feasibility and effectiveness of the proposed method. The results show that it has a better performance than traditional scheduling methods. CO 2021 Elsevier B.V. All rights reserved.
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