Automated Design of Production Scheduling Heuristics: A Review
journal contribution
posted on 2020-10-28, 03:06 authored by J Branke, S Nguyen, CW Pickardt, Mengjie ZhangMengjie Zhang© 1997-2012 IEEE. Hyper-heuristics have recently emerged as a powerful approach to automate the design of heuristics for a number of different problems. Production scheduling is a particularly popular application area for which a number of different hyper-heuristics have been developed and are shown to be effective, efficient, easy to implement, and reusable in different shop conditions. In particular, they seem to be a promising way to tackle highly dynamic and stochastic scheduling problems, an aspect that is specifically emphasized in this survey. Despite their success and the substantial number of papers in this area, there is currently no systematic discussion of the design choices and critical issues involved in the process of developing such approaches. This paper strives to fill this gap by summarizing the state-of-the-art approaches, suggesting a taxonomy, and providing the interested researchers and practitioners with guidelines for the design of hyper-heuristics in production scheduling. This paper also identifies challenges and open questions and highlights various directions for future work.
History
Preferred citation
Branke, J., Nguyen, S., Pickardt, C. W. & Zhang, M. (2016). Automated Design of Production Scheduling Heuristics: A Review. IEEE Transactions on Evolutionary Computation, 20(1), 110-124. https://doi.org/10.1109/TEVC.2015.2429314Publisher DOI
Journal title
IEEE Transactions on Evolutionary ComputationVolume
20Issue
1Publication date
2016-02-01Pagination
110-124Publisher
Institute of Electrical and Electronics Engineers (IEEE)Publication status
PublishedISSN
1089-778XeISSN
1941-0026Usage metrics
Categories
Keywords
Licence
Exports
RefWorksRefWorks
BibTeXBibTeX
Ref. managerRef. manager
EndnoteEndnote
DataCiteDataCite
NLMNLM
DCDC