Hybrid multi-objective opposite-learning evolutionary algorithm for integrated production and maintenance scheduling with energy consideration
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-020-05075-3.pdf
Reference49 articles.
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2. Zhou BH, Yi Q, Liu YW (2020) Proactive preventive maintenance policy for buffered serial production systems based on energy saving opportunistic windows. J Cleaner Prod 253:119791. https://doi.org/10.1016/j.jclepro.2019.119791
3. Mohammad JR, Raheb B (2018) Haulage system selection for open pit mines using fuzzy MCDM and the view on energy saving. Neural Comput Appl 29:187–199. https://doi.org/10.1007/s00521-016-2562-7
4. Lv JX, Peng T, Tang RZ (2019) Energy modeling and a method for reducing energy loss due to cutting load during machining operations. Proc Institution Mech Eng Part B J Eng Manuf 233(3):699–710. https://doi.org/10.1177/0954405418769922
5. Li SJ, Liu F, Zhou XN (2018) Multi-objective energy-saving scheduling for a permutation flow line. Proc Institution Mech Eng Part B J Eng Manuf 232(5):879–888. https://doi.org/10.1177/0954405416657583
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