Crossover control in selection hyper-heuristics: case studies using MKP and HyFlex
Hyper-heuristics are a class of high-level search methodologies which operate over a search space of heuristics rather than a search space of solutions. Hyper-heuristic research has set out to develop methods which are more general than traditional search and optimisation techniques. In recent years...
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| Format: | Thesis (University of Nottingham only) |
| Language: | English |
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2014
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| Online Access: | https://eprints.nottingham.ac.uk/14276/ |
| _version_ | 1848791920022650880 |
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| author | Drake, John H. |
| author_facet | Drake, John H. |
| 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 over a search space of heuristics rather than a search space of solutions. Hyper-heuristic research has set out to develop methods which are more general than traditional search and optimisation techniques. In recent years, focus has shifted considerably towards cross-domain heuristic search. The intention is to develop methods which are able to deliver an acceptable level of performance over a variety of different problem domains, given a set of low-level heuristics to work with.
This thesis presents a body of work investigating the use of selection hyper-heuristics in a number of different problem domains. Specifically the use of crossover operators, prevalent in many evolutionary algorithms, is explored within the context of single-point search hyper-heuristics. A number of traditional selection hyper-heuristics are applied to instances of a well-known NP-hard combinatorial optimisation problem, the multidimensional knapsack problem. This domain is chosen as a benchmark for the variety of existing problem instances and solution methods available. The results suggest that selection hyper-heuristics are a viable method to solve some instances of this problem domain. Following this, a framework is defined to describe the conceptual level at which crossover low-level heuristics are managed in single-point selection hyper-heuristics. HyFlex is an existing software framework which supports the design of heuristic search methods over multiple problem domains, i.e. cross-domain optimisation. A traditional heuristic selection mechanism is modified in order to improve results in the context of cross-domain optimisation. Finally the effect of crossover use in cross-domain optimisation is explored. |
| first_indexed | 2025-11-14T18:36:10Z |
| format | Thesis (University of Nottingham only) |
| id | nottingham-14276 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T18:36:10Z |
| publishDate | 2014 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-142762025-02-28T11:29:49Z https://eprints.nottingham.ac.uk/14276/ Crossover control in selection hyper-heuristics: case studies using MKP and HyFlex Drake, John H. Hyper-heuristics are a class of high-level search methodologies which operate over a search space of heuristics rather than a search space of solutions. Hyper-heuristic research has set out to develop methods which are more general than traditional search and optimisation techniques. In recent years, focus has shifted considerably towards cross-domain heuristic search. The intention is to develop methods which are able to deliver an acceptable level of performance over a variety of different problem domains, given a set of low-level heuristics to work with. This thesis presents a body of work investigating the use of selection hyper-heuristics in a number of different problem domains. Specifically the use of crossover operators, prevalent in many evolutionary algorithms, is explored within the context of single-point search hyper-heuristics. A number of traditional selection hyper-heuristics are applied to instances of a well-known NP-hard combinatorial optimisation problem, the multidimensional knapsack problem. This domain is chosen as a benchmark for the variety of existing problem instances and solution methods available. The results suggest that selection hyper-heuristics are a viable method to solve some instances of this problem domain. Following this, a framework is defined to describe the conceptual level at which crossover low-level heuristics are managed in single-point selection hyper-heuristics. HyFlex is an existing software framework which supports the design of heuristic search methods over multiple problem domains, i.e. cross-domain optimisation. A traditional heuristic selection mechanism is modified in order to improve results in the context of cross-domain optimisation. Finally the effect of crossover use in cross-domain optimisation is explored. 2014 Thesis (University of Nottingham only) NonPeerReviewed application/pdf en arr https://eprints.nottingham.ac.uk/14276/1/thesis.pdf Drake, John H. (2014) Crossover control in selection hyper-heuristics: case studies using MKP and HyFlex. PhD thesis, University of Nottingham. hyper-heuristics heuristic programming knapsack problem algorithms search |
| spellingShingle | hyper-heuristics heuristic programming knapsack problem algorithms search Drake, John H. Crossover control in selection hyper-heuristics: case studies using MKP and HyFlex |
| title | Crossover control in selection hyper-heuristics: case studies using MKP and HyFlex |
| title_full | Crossover control in selection hyper-heuristics: case studies using MKP and HyFlex |
| title_fullStr | Crossover control in selection hyper-heuristics: case studies using MKP and HyFlex |
| title_full_unstemmed | Crossover control in selection hyper-heuristics: case studies using MKP and HyFlex |
| title_short | Crossover control in selection hyper-heuristics: case studies using MKP and HyFlex |
| title_sort | crossover control in selection hyper-heuristics: case studies using mkp and hyflex |
| topic | hyper-heuristics heuristic programming knapsack problem algorithms search |
| url | https://eprints.nottingham.ac.uk/14276/ |