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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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2016
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| Subjects: | |
| Online Access: | http://repo.uum.edu.my/18475/1/IASC%202016%201-8.pdf http://repo.uum.edu.my/18475/ http://doi.org/10.1080/10798587.2016.1177914 |
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| Summary: | 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. |
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