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ACOustic: A nature-inspired exploration indicator for ant colony optimization

Sagban, Rafid and Ku-Mahamud, Ku Ruhana and Abu Bakar, Muhamad Shahbani (2015) ACOustic: A nature-inspired exploration indicator for ant colony optimization. The Scientific World Journal, 2015. pp. 1-11. ISSN 2356-6140

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A statistical machine learning indicator, ACOustic, is proposed to evaluate the exploration behavior in the iterations of ant colony optimization algorithms. This idea is inspired by the behavior of some parasites in their mimicry to the queens’ acoustics of their ant hosts.The parasites’ reaction results from their ability to indicate the state of penetration.The proposed indicator solves the problem of robustness that results from the difference of magnitudes in the distance’s matrix, especially when combinatorial optimization problems with rugged fitness landscape are applied.The performance of the proposed indicator is evaluated against the existing indicators in six variants of ant colony optimization algorithms.Instances for travelling salesman problem and quadratic assignment problem are used in the experimental evaluation.The analytical results showed that the proposed indicator is more informative and more robust.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: School of Computing
Depositing User: Prof. Dr. Ku Ruhana Ku Mahamud
Date Deposited: 06 Jul 2015 06:41
Last Modified: 27 Apr 2016 08:38
URI: http://repo.uum.edu.my/id/eprint/14740

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