An analysis of the Taguchi method for tuning a memetic algorithm with reduced computational time budget
Determining the best initial parameter values for an algorithm, called parameter tuning, is crucial to obtaining better algorithm performance; however, it is often a time-consuming task and needs to be performed under a restricted computational budget. In this study, the results from our previous wo...
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| Format: | Book Section |
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Springer
2016
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| Online Access: | https://eprints.nottingham.ac.uk/37338/ |
| _version_ | 1848795439259713536 |
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| author | Gümüş, Düriye Betül Özcan, Ender Atkin, Jason |
| author_facet | Gümüş, Düriye Betül Özcan, Ender Atkin, Jason |
| author_sort | Gümüş, Düriye Betül |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Determining the best initial parameter values for an algorithm, called parameter tuning, is crucial to obtaining better algorithm performance; however, it is often a time-consuming task and needs to be performed under a restricted computational budget. In this study, the results from our previous work on using the Taguchi method to tune the parameters of a memetic algorithm for cross-domain search are further analysed and extended. Although the Taguchi method reduces the time spent finding a good parameter value combination by running a smaller size of experiments on the training instances from different domains as opposed to evaluating all combinations, the time budget is still larger than desired. This work investigates the degree to which it is possible to predict the same good parameter setting faster by using a reduced time budget. The results in this paper show that it was possible to predict good combinations of parameter settings with a much reduced time budget. The good final parameter values are predicted for three of the parameters, while for the fourth parameter there is no clear best value, so one of three similarly performing values is identified at each time instant. |
| first_indexed | 2025-11-14T19:32:06Z |
| format | Book Section |
| id | nottingham-37338 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:32:06Z |
| publishDate | 2016 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-373382020-05-04T18:09:48Z https://eprints.nottingham.ac.uk/37338/ An analysis of the Taguchi method for tuning a memetic algorithm with reduced computational time budget Gümüş, Düriye Betül Özcan, Ender Atkin, Jason Determining the best initial parameter values for an algorithm, called parameter tuning, is crucial to obtaining better algorithm performance; however, it is often a time-consuming task and needs to be performed under a restricted computational budget. In this study, the results from our previous work on using the Taguchi method to tune the parameters of a memetic algorithm for cross-domain search are further analysed and extended. Although the Taguchi method reduces the time spent finding a good parameter value combination by running a smaller size of experiments on the training instances from different domains as opposed to evaluating all combinations, the time budget is still larger than desired. This work investigates the degree to which it is possible to predict the same good parameter setting faster by using a reduced time budget. The results in this paper show that it was possible to predict good combinations of parameter settings with a much reduced time budget. The good final parameter values are predicted for three of the parameters, while for the fourth parameter there is no clear best value, so one of three similarly performing values is identified at each time instant. Springer 2016-09-24 Book Section PeerReviewed Gümüş, Düriye Betül, Özcan, Ender and Atkin, Jason (2016) An analysis of the Taguchi method for tuning a memetic algorithm with reduced computational time budget. In: Computer and information sciences: 31st International Symposium, ISCIS 2016, Kraków, Poland, October 27–28, 2016, proceedings. Communications in computer and information science, 659 (659). Springer, pp. 12-20. ISBN 978-3-319-47217-1 Evolutionary algorithm; Parameter tuning; Design of experiments; Hyper-heuristic; Optimisation http://link.springer.com/chapter/10.1007%2F978-3-319-47217-1_2 doi:10.1007/978-3-319-47217-1_2 doi:10.1007/978-3-319-47217-1_2 |
| spellingShingle | Evolutionary algorithm; Parameter tuning; Design of experiments; Hyper-heuristic; Optimisation Gümüş, Düriye Betül Özcan, Ender Atkin, Jason An analysis of the Taguchi method for tuning a memetic algorithm with reduced computational time budget |
| title | An analysis of the Taguchi method for tuning a memetic algorithm with reduced computational time budget |
| title_full | An analysis of the Taguchi method for tuning a memetic algorithm with reduced computational time budget |
| title_fullStr | An analysis of the Taguchi method for tuning a memetic algorithm with reduced computational time budget |
| title_full_unstemmed | An analysis of the Taguchi method for tuning a memetic algorithm with reduced computational time budget |
| title_short | An analysis of the Taguchi method for tuning a memetic algorithm with reduced computational time budget |
| title_sort | analysis of the taguchi method for tuning a memetic algorithm with reduced computational time budget |
| topic | Evolutionary algorithm; Parameter tuning; Design of experiments; Hyper-heuristic; Optimisation |
| url | https://eprints.nottingham.ac.uk/37338/ https://eprints.nottingham.ac.uk/37338/ https://eprints.nottingham.ac.uk/37338/ |