Reactive max-min ant system with recursive local search and its application to TSP and QAP
Ant colony optimization is a successful metaheuristic for solving combinatorial optimization problems. However, the drawback of premature exploitation arises in ant colony optimization when coupled with local searches, in which the neighborhood’s structures of the search space are not completely...
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Format: | Article |
Language: | English |
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Taylor & Francis Group
2016
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Online Access: | https://repo.uum.edu.my/id/eprint/18475/1/IASC%202016%201-8.pdf |
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author | Sagban, Rafid Ku-Mahamud, Ku Ruhana Abu Bakar, Muhamad Shahbani |
author_facet | Sagban, Rafid Ku-Mahamud, Ku Ruhana Abu Bakar, Muhamad Shahbani |
author_sort | Sagban, Rafid |
collection | UUM |
description | Ant colony optimization is a successful metaheuristic for solving combinatorial optimization problems.
However, the drawback of premature exploitation arises in ant colony optimization when coupled
with local searches, in which the neighborhood’s structures of the search space are not completely
traversed.This paper proposes two algorithmic components for solving the premature exploitation, i.e. the reactive heuristics and recursive local search technique.The resulting algorithm is tested on two well-known combinatorial optimization problems arising in the artificial intelligence problems field
and compared experimentally to six (6) variants of ACO with local search. Results showed that the
enhanced algorithm outperforms the six ACO variants. |
first_indexed | 2024-07-04T06:07:53Z |
format | Article |
id | uum-18475 |
institution | Universiti Utara Malaysia |
language | English |
last_indexed | 2024-07-04T06:07:53Z |
publishDate | 2016 |
publisher | Taylor & Francis Group |
record_format | eprints |
spelling | uum-184752016-08-08T04:16:34Z https://repo.uum.edu.my/id/eprint/18475/ Reactive max-min ant system with recursive local search and its application to TSP and QAP Sagban, Rafid Ku-Mahamud, Ku Ruhana Abu Bakar, Muhamad Shahbani QA75 Electronic computers. Computer science Ant colony optimization is a successful metaheuristic for solving combinatorial optimization problems. However, the drawback of premature exploitation arises in ant colony optimization when coupled with local searches, in which the neighborhood’s structures of the search space are not completely traversed.This paper proposes two algorithmic components for solving the premature exploitation, i.e. the reactive heuristics and recursive local search technique.The resulting algorithm is tested on two well-known combinatorial optimization problems arising in the artificial intelligence problems field and compared experimentally to six (6) variants of ACO with local search. Results showed that the enhanced algorithm outperforms the six ACO variants. Taylor & Francis Group 2016 Article PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/18475/1/IASC%202016%201-8.pdf Sagban, Rafid and Ku-Mahamud, Ku Ruhana and Abu Bakar, Muhamad Shahbani (2016) Reactive max-min ant system with recursive local search and its application to TSP and QAP. Intelligent Automation & Soft Computing. pp. 1-8. ISSN 1079-8587 http://doi.org/10.1080/10798587.2016.1177914 doi:10.1080/10798587.2016.1177914 doi:10.1080/10798587.2016.1177914 |
spellingShingle | QA75 Electronic computers. Computer science Sagban, Rafid Ku-Mahamud, Ku Ruhana Abu Bakar, Muhamad Shahbani Reactive max-min ant system with recursive local search and its application to TSP and QAP |
title | Reactive max-min ant system with recursive local search and its application to TSP and QAP |
title_full | Reactive max-min ant system with recursive local search and its application to TSP and QAP |
title_fullStr | Reactive max-min ant system with recursive local search and its application to TSP and QAP |
title_full_unstemmed | Reactive max-min ant system with recursive local search and its application to TSP and QAP |
title_short | Reactive max-min ant system with recursive local search and its application to TSP and QAP |
title_sort | reactive max min ant system with recursive local search and its application to tsp and qap |
topic | QA75 Electronic computers. Computer science |
url | https://repo.uum.edu.my/id/eprint/18475/1/IASC%202016%201-8.pdf |
work_keys_str_mv | AT sagbanrafid reactivemaxminantsystemwithrecursivelocalsearchanditsapplicationtotspandqap AT kumahamudkuruhana reactivemaxminantsystemwithrecursivelocalsearchanditsapplicationtotspandqap AT abubakarmuhamadshahbani reactivemaxminantsystemwithrecursivelocalsearchanditsapplicationtotspandqap |