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

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Abstract

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.

Item Type:	Article
Uncontrolled Keywords:	Optimization; combinatorial problems; metaheuristics; swarm intelligence; search algorithms; ant colony optimization; recursive local search; reactive heuristics; traveling salesman problem; quadratic assignment problem
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	School of Computing
Depositing User:	Prof. Dr. Ku Ruhana Ku Mahamud
Date Deposited:	08 Aug 2016 04:16
Last Modified:	08 Aug 2016 04:16
URI:	https://repo.uum.edu.my/id/eprint/18475

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