Comparative evaluation of tabu search hyper-heuristic against its low-level meta-heuristic constituents
Hyper-heuristics present a superior form of hybridization of meta-heuristics. Unlike typical meta-heuristic hybridization, which requires low-level integration of two or more metaheuristics, hyper-heuristics offer meta level separation (as domain barrier) of each participating low-level meta-heurist...
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| Language: | en en |
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2019
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| Online Access: | http://umpir.ump.edu.my/id/eprint/25464/1/55.%20Comprative%20evaluation%20of%20tabu%20search%20hyper-heuristic.pdf http://umpir.ump.edu.my/id/eprint/25464/2/55.1%20Comprative%20evaluation%20of%20tabu%20search%20hyper-heuristic.pdf http://umpir.ump.edu.my/id/eprint/25464/ |
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| author | Fakhrud, Din Kamal Z., Zamli |
| author_facet | Fakhrud, Din Kamal Z., Zamli |
| author_sort | Fakhrud, Din |
| building | UMPSA Library |
| collection | Institutional Repository |
| content_provider | Universiti Malaysia Pahang Al-Sultan Abdullah |
| content_source | UMPSA Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Hyper-heuristics present a superior form of hybridization of meta-heuristics. Unlike typical meta-heuristic hybridization, which requires low-level integration of two or more metaheuristics, hyper-heuristics offer meta level separation (as domain barrier) of each participating low-level meta-heuristic and permit adaptive selection between them. Owing to the prospects of improving the generality of its application to general optimization problems, this paper evaluates the performance of a Tabu search based hyper-heuristic (called HHH) against its individual low-level meta-heuristic (LLH) constituents. The results based on its application to t-way test suite generation problem indicate that HHH outperforms all its individual LLH constituents consisting of particle swarm optimization (PSO), global neighbourhood algorithm (GNA), cuckoo search (CS) algorithm and teaching learning-based opthnization algorithm (TLBO). However, there is a time performance penalty as overhead to perform the nmtime adaptive selection of each LLH. |
| format | Conference or Workshop Item |
| id | my.ump.umpir.25464 |
| institution | Universiti Malaysia Pahang |
| language | en en |
| publishDate | 2019 |
| record_format | eprints |
| spelling | my.ump.umpir.254642020-01-10T08:06:31Z http://umpir.ump.edu.my/id/eprint/25464/ Comparative evaluation of tabu search hyper-heuristic against its low-level meta-heuristic constituents Fakhrud, Din Kamal Z., Zamli QA76 Computer software Hyper-heuristics present a superior form of hybridization of meta-heuristics. Unlike typical meta-heuristic hybridization, which requires low-level integration of two or more metaheuristics, hyper-heuristics offer meta level separation (as domain barrier) of each participating low-level meta-heuristic and permit adaptive selection between them. Owing to the prospects of improving the generality of its application to general optimization problems, this paper evaluates the performance of a Tabu search based hyper-heuristic (called HHH) against its individual low-level meta-heuristic (LLH) constituents. The results based on its application to t-way test suite generation problem indicate that HHH outperforms all its individual LLH constituents consisting of particle swarm optimization (PSO), global neighbourhood algorithm (GNA), cuckoo search (CS) algorithm and teaching learning-based opthnization algorithm (TLBO). However, there is a time performance penalty as overhead to perform the nmtime adaptive selection of each LLH. 2019 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/25464/1/55.%20Comprative%20evaluation%20of%20tabu%20search%20hyper-heuristic.pdf pdf en http://umpir.ump.edu.my/id/eprint/25464/2/55.1%20Comprative%20evaluation%20of%20tabu%20search%20hyper-heuristic.pdf Fakhrud, Din and Kamal Z., Zamli (2019) Comparative evaluation of tabu search hyper-heuristic against its low-level meta-heuristic constituents. In: 3rd International Conference On Computational Science And Information Managemant (ICOCSIM19) , 20 - 23 March 2019 , Aruna Senggiri Resort And Convention Hotel,Lombok. pp. 1-6.. (Unpublished) (Unpublished) |
| spellingShingle | QA76 Computer software Fakhrud, Din Kamal Z., Zamli Comparative evaluation of tabu search hyper-heuristic against its low-level meta-heuristic constituents |
| title | Comparative evaluation of tabu search hyper-heuristic against its low-level meta-heuristic constituents |
| title_full | Comparative evaluation of tabu search hyper-heuristic against its low-level meta-heuristic constituents |
| title_fullStr | Comparative evaluation of tabu search hyper-heuristic against its low-level meta-heuristic constituents |
| title_full_unstemmed | Comparative evaluation of tabu search hyper-heuristic against its low-level meta-heuristic constituents |
| title_short | Comparative evaluation of tabu search hyper-heuristic against its low-level meta-heuristic constituents |
| title_sort | comparative evaluation of tabu search hyper-heuristic against its low-level meta-heuristic constituents |
| topic | QA76 Computer software |
| url | http://umpir.ump.edu.my/id/eprint/25464/1/55.%20Comprative%20evaluation%20of%20tabu%20search%20hyper-heuristic.pdf http://umpir.ump.edu.my/id/eprint/25464/2/55.1%20Comprative%20evaluation%20of%20tabu%20search%20hyper-heuristic.pdf http://umpir.ump.edu.my/id/eprint/25464/ |
| url_provider | http://umpir.ump.edu.my/ |