期刊
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
卷 56, 期 1-2, 页码 193-223出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207543.2018.1437288
关键词
evolutionary algorithm; machine learning; scheduling; combinatorial optimisation; hybrid algorithm; scheduling application
资金
- National Natural Science Foundation of China [61572100]
- Japan Society of Promotion of Science [15K00357]
- Grants-in-Aid for Scientific Research [15K00357] Funding Source: KAKEN
Evolutionary Algorithms (EAs) has attracted significantly attention with respect to complexity scheduling problems, which is referred to evolutionary scheduling. However, EAs differ in the implementation details and the nature of the particular scheduling problem applied. In order to have an effective implementation of EAs for production scheduling, this paper focuses on making a survey of researches based on using hybrid EAs. Starting from scheduling description, we identify the classification and graph representation of scheduling problems. Then, we present the various representations, hybridisation techniques and machine-learning techniques to enhancing EAs. Finally, we also present successful applications in manufacturing.
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