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