Dimopoulos, C. and Zalzala, A. (1998) Investigating the Use of Genetic Programming for a Classic One-Machine Scheduling Problem. Research Report. ACSE Research Report 737 . Department of Automatic Control and Systems Engineering
Abstract
Genetic programming has rarely been applied to manufacturing optimisation problems.In this report we investigate the potential use of Genetic Programming for the solution of one-machine total tardiness problem. Combinations of dispatching rules are employed as an indirect way of representing permutations within a Genetic Programming framework. Hybridisation of Genetic Programming with local search techniques is also introduced, in an attempt to improve the quality of solutions. Finally, Genetic Programming is utilised for the evolution of scheduling policies in the form of dispatching rules. These rules are trained to cope with different levels of tardiness and tightness of due dates.
Metadata
Item Type: | Monograph |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | The Department of Automatic Control and Systems Engineering research reports offer a forum for the research output of the academic staff and research students of the Department at the University of Sheffield. Papers are reviewed for quality and presentation by a departmental editor. However, the contents and opinions expressed remain the responsibility of the authors. Some papers in the series may have been subsequently published elsewhere and you are advised to cite the later published version in these instances. |
Keywords: | Evolutionary Computation; Genetic Programming; Manufacturing Optimisation, Tardiness, Scheduling |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) > ACSE Research Reports |
Depositing User: | MRS ALISON THERESA BARNETT |
Date Deposited: | 17 Dec 2014 12:30 |
Last Modified: | 24 Oct 2016 23:39 |
Status: | Published |
Publisher: | Department of Automatic Control and Systems Engineering |
Series Name: | ACSE Research Report 737 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:82572 |