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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 neighborhood2019s 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.



Total Pages: 8
Pages: 127-134


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Volume: 23
Issue: 1
Year: 2016

Cite this document


Battiti R. Reactive search and intelligent optimization

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ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)
Journal: 1995-Present


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