- author = "Juergen Branke and Su Nguyen and Christoph Pickardt and Mengjie Zhang",
- title = "Automated Design of Production Scheduling Heuristics: A Review",
- journal = "IEEE Transactions on Evolutionary Computation",
- year = "2016",
- volume = "20",
- number = "1",
- pages = "110--124",
- month = feb,
- keywords = "genetic algorithms, genetic programming, Evolutionary design, hyper-heuristic, scheduling.",
- ISSN = "1089-778X",
-
URL = "
http://wrap.warwick.ac.uk/88212/1/WRAP-automated-design-production-scheduling-heuristics-Branke-2015.pdf",
-
URL = "
http://wrap.warwick.ac.uk/88212/",
-
DOI = "
doi:10.1109/TEVC.2015.2429314",
- size = "15 pages",
- abstract = "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 hyperheuristics have been developed and shown to be effective, efficient, easy to implement, and reusable in different shop conditions. In particular, they seem a promising way to tackle highly dynamic and stochastic scheduling problems, an aspect that is specifically emphasised 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 review strives to fill this gap by summarising the state of the art, 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.",
-
notes = "This paper is a review mainly on GP methods for
scheduling.
Also known as \cite{7101236}",
