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Automated Design of Production Scheduling Heuristics: A Review

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journal contribution
posted on 28.10.2020, 03:06 by J Branke, S Nguyen, CW Pickardt, Mengjie 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.2015.2429314

Journal title

IEEE Transactions on Evolutionary Computation

Volume

20

Issue

1

Publication date

01/02/2016

Pagination

110-124

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Publication status

Published

ISSN

1089-778X

eISSN

1941-0026

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