A Novel Ant Colony Optimization Algorithm With Levy Flight

Ant Colony Optimization (ACO) is a widely applied meta-heuristic algorithm. Little researches focused on the candidate selection mechanism, which was developed based on the simple uniform distribution. This paper employs the Levy flight mechanism based on Levy distribution to the candidate selection...

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Bibliographic Details
Published in:IEEE access 2020, Vol.8, p.67205-67213
Main Authors: Liu, Yahui, Cao, Buyang
Format: Article
Language:English
Subjects:
Algorithms
Ant colony optimization
Heuristic methods
Indexes
Levy distribution
Levy flight
Optimization
Performance enhancement
Random variables
Reinforcement learning
Solvers
Space exploration
Traveling salesman problem
Traveling salesman problems
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Summary:Ant Colony Optimization (ACO) is a widely applied meta-heuristic algorithm. Little researches focused on the candidate selection mechanism, which was developed based on the simple uniform distribution. This paper employs the Levy flight mechanism based on Levy distribution to the candidate selection process and takes advantage of Levy flight that not only guarantees the search speed but also extends the searching space to improve the performance of ACO. Levy ACO incorporating with Levy flight developed on the top of Max-min ACO. According to the computational experiments, the performance of Levy ACO is significantly better than the original Max-min ACO and some latest Traveling Salesman Problem (TSP) solvers.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.2985498