A modified choice function hyper-heuristic controlling unary and binary operators
Hyper-heuristics are a class of high-level search methodologies which operate on a search space of low-level heuristics or components, rather than on solutions directly. Traditional iterative selection hyper-heuristics rely on two key components, a heuristic selection method and a move acceptance cr...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Published: |
2015
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| Online Access: | https://eprints.nottingham.ac.uk/33943/ |
| _version_ | 1848794739753615360 |
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| author | Drake, John H. Özcan, Ender Burke, Edmund K. |
| author_facet | Drake, John H. Özcan, Ender Burke, Edmund K. |
| author_sort | Drake, John H. |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Hyper-heuristics are a class of high-level search methodologies which operate on a search space of low-level heuristics or components, rather than on solutions directly. Traditional iterative selection hyper-heuristics rely on two key components, a heuristic selection method and a move acceptance criterion. Choice Function heuristic selection scores heuristics based on a combination of three measures, selecting the heuristic with the highest score. Modified Choice Function heuristic selection is a variant of the Choice Function which emphasises intensification over diversification within the heuristic search process. Previous work has shown that improved results are possible in some problem domains when using Modified Choice Function heuristic selection over the classic Choice Function, however in most of these cases crossover low-level heuristics (operators) are omitted. In this paper, we introduce crossover low-level heuristics into a Modified Choice Function selection hyper-heuristic and present results over six problem domains. It is observed that although on average there is an increase in performance when using crossover low-level heuristics, the benefit of using crossover can vary on a per-domain or per-instance basis. |
| first_indexed | 2025-11-14T19:20:59Z |
| format | Conference or Workshop Item |
| id | nottingham-33943 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:20:59Z |
| publishDate | 2015 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-339432020-05-04T17:08:06Z https://eprints.nottingham.ac.uk/33943/ A modified choice function hyper-heuristic controlling unary and binary operators Drake, John H. Özcan, Ender Burke, Edmund K. Hyper-heuristics are a class of high-level search methodologies which operate on a search space of low-level heuristics or components, rather than on solutions directly. Traditional iterative selection hyper-heuristics rely on two key components, a heuristic selection method and a move acceptance criterion. Choice Function heuristic selection scores heuristics based on a combination of three measures, selecting the heuristic with the highest score. Modified Choice Function heuristic selection is a variant of the Choice Function which emphasises intensification over diversification within the heuristic search process. Previous work has shown that improved results are possible in some problem domains when using Modified Choice Function heuristic selection over the classic Choice Function, however in most of these cases crossover low-level heuristics (operators) are omitted. In this paper, we introduce crossover low-level heuristics into a Modified Choice Function selection hyper-heuristic and present results over six problem domains. It is observed that although on average there is an increase in performance when using crossover low-level heuristics, the benefit of using crossover can vary on a per-domain or per-instance basis. 2015-05-25 Conference or Workshop Item PeerReviewed Drake, John H., Özcan, Ender and Burke, Edmund K. (2015) A modified choice function hyper-heuristic controlling unary and binary operators. In: 2015 IEEE Congress on Evolutionary Computation (CEC2015), 25-28 May 2015, Sendai, Japan. http://dx.doi.org/10.1109/CEC.2015.7257315 10.1109/CEC.2015.7257315 10.1109/CEC.2015.7257315 10.1109/CEC.2015.7257315 |
| spellingShingle | Drake, John H. Özcan, Ender Burke, Edmund K. A modified choice function hyper-heuristic controlling unary and binary operators |
| title | A modified choice function hyper-heuristic controlling unary and binary operators |
| title_full | A modified choice function hyper-heuristic controlling unary and binary operators |
| title_fullStr | A modified choice function hyper-heuristic controlling unary and binary operators |
| title_full_unstemmed | A modified choice function hyper-heuristic controlling unary and binary operators |
| title_short | A modified choice function hyper-heuristic controlling unary and binary operators |
| title_sort | modified choice function hyper-heuristic controlling unary and binary operators |
| url | https://eprints.nottingham.ac.uk/33943/ https://eprints.nottingham.ac.uk/33943/ https://eprints.nottingham.ac.uk/33943/ |