Dr ANDREW PARKES ANDREW.PARKES@NOTTINGHAM.AC.UK
Associate Professor
A software interface for supporting the application of data science to optimisation
Parkes, Andrew J.; �zcan, Ender; Karapetyan, Daniel
Authors
ENDER OZCAN ender.ozcan@nottingham.ac.uk
Professor of Computer Science and Operational Research
Daniel Karapetyan
Abstract
Many real world problems can be solved effectively by metaheuristics in combination with neighbourhood search. However, implementing neighbourhood search for a particular problem domain can be time consuming and so it is important to get the most value from it. Hyper-heuristics aim to get such value by using a specific API such as
`HyFlex' to cleanly separate the search control structure from the details of the domain. Here, we discuss various longer-term additions to the HyFlex interface that will allow much richer information exchange, and so enhance learning via data science techniques, but without losing domain independence of the search control.
Citation
Parkes, A. J., Özcan, E., & Karapetyan, D. (2015). A software interface for supporting the application of data science to optimisation. Lecture Notes in Artificial Intelligence, 8994, 306-311. https://doi.org/10.1007/978-3-319-19084-6_31
Journal Article Type | Article |
---|---|
Acceptance Date | Jan 15, 2015 |
Publication Date | May 29, 2015 |
Deposit Date | Jun 13, 2016 |
Publicly Available Date | Jun 13, 2016 |
Journal | Lecture Notes in Computer Science |
Electronic ISSN | 0302-9743 |
Publisher | Springer Verlag |
Peer Reviewed | Peer Reviewed |
Volume | 8994 |
Pages | 306-311 |
Series Title | Lecture Notes in Computer Science |
Book Title | Learning and Intelligent Optimization |
DOI | https://doi.org/10.1007/978-3-319-19084-6_31 |
Keywords | combinatorial optimization, metaheuristics, data science, machine learning |
Public URL | https://nottingham-repository.worktribe.com/output/751054 |
Publisher URL | http://link.springer.com/chapter/10.1007%2F978-3-319-19084-6_31 |
Additional Information | In chapter: Learning and intelligent optimization. ISBN 9783319190839. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-19084-6_31. |
Files
software-interface-data-science-optimisation.pdf
(157 Kb)
PDF
Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0
You might also like
CUDA-based parallel local search for the set-union knapsack problem
(2024)
Journal Article
A benchmark dataset for multi-objective flexible job shop cell scheduling
(2023)
Journal Article
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search