Dou, T. and Rockett, P.I. orcid.org/0000-0002-4636-7727 (2017) Semantic-based local search in multiobjective genetic programming. In: GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference. Genetic and Evolutionary Computation Conference, 15-19 Jul 2017, Berlin, Germany. ACM ISBN 978-1-4503-4939-0
Abstract
We report a series of experiments within a multiobjective genetic programming (GP) framework using semantic-based local GP search. We have made comparison with the Random Desired Operator (RDO) of Pawlak et al. and find that a standard generational GP followed by a carefully-designed single-objective GP implementing semantic-based local search yields results statistically comparable to those obtained with the RDO operator. The trees obtained with our GP-based local search technique are, however, around half the size of the trees resulting from the use of the RDO.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 ACM. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 03 Jul 2017 14:54 |
Last Modified: | 05 Oct 2018 13:28 |
Published Version: | https://doi.org/10.1145/3067695.3076015 |
Status: | Published |
Publisher: | ACM |
Refereed: | Yes |
Identification Number: | 10.1145/3067695.3076015 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:117260 |