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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Liang Wan Xinyu Li Liang Gao Xiaoyu Wen Wenwen Wang |
| Copyright Year | 2013 |
| Description | Author affiliation: State Key Lab. of Digital Manuf. Equip. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China (Liang Wan; Xinyu Li; Liang Gao; Xiaoyu Wen; Wenwen Wang) |
| Abstract | Process planning and scheduling are two important sub-systems in modern manufacturing system. In manufacturing system, the two sub-systems of process planning and scheduling have been treated sequentially or separately in traditional methods. To increase the effectiveness of system performance, there is an increasing need for deep research and application of integrated process planning and scheduling (IPPS) system. In this paper, a novel two-level genetic algorithm (TGA) is proposed to optimize the IPPS problem. Based on the previous work, deep research should be made on the IPPS problem. In this study, the flow chart of TGA based on the previous integrated optimization strategy has been proposed. Experiment studies have been conducted to verify the performance of the proposed algorithm. The experimental results show that the proposed algorithm for the IPPS is a promising and very effective method. |
| Sponsorship | IEEE Syst., Man, Cybern. Soc. |
| Starting Page | 2790 |
| Ending Page | 2795 |
| File Size | 581957 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781479906529 |
| DOI | 10.1109/SMC.2013.476 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-10-13 |
| Publisher Place | UK |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Process planning Job shop scheduling Genetic algorithms Sociology Statistics Biological cells Optimization improved genetic algorithm scheduling integrated process planning and scheduling |
| Content Type | Text |
| Resource Type | Article |
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