Automated Design of Production Scheduling Heuristics: A Review

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,...

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Bibliographic Details
Published in:IEEE transactions on evolutionary computation 2016-02, Vol.20 (1), p.110-124
Main Authors: Branke, Jurgen, Su Nguyen, Pickardt, Christoph W., Mengjie Zhang
Format: Article
Language:English
Subjects:
Design engineering
Dispatching
Dynamic scheduling
Dynamics
evolutionary design
genetic programming
Guidelines
Heuristic
hyper-heuristic
Job shop scheduling
Processor scheduling
Production scheduling
Schedules
Scheduling
Space exploration
State of the art
Stochasticity
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Summary: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.
ISSN:1089-778X
1941-0026
DOI:10.1109/TEVC.2015.2429314