Improved robustness through population variance in ant colony optimization

David C. Matthews; Andrew M. Sutton; Doug Hains; L. Darrell Whitley

doi:10.1007/978-3-642-03751-1_16

Improved robustness through population variance in ant colony optimization

David C. Matthews, Andrew M. Sutton, Doug Hains, L. Darrell Whitley

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

Abstract

Ant Colony Optimization algorithms are population-based Stochastic Local Search algorithms that mimic the behavior of ants, simulating pheromone trails to search for solutions to combinatorial optimization problems. This paper introduces Population Variance, a novel approach to ACO algorithms that allows parameters to vary across the population over time, leading to solution construction differences that are not strictly stochastic. The increased exploration appears to help the search escape from local optima, significantly improving the robustness of the algorithm with respect to suboptimal parameter settings.

Original language	English (US)
Title of host publication	Engineering Stochastic Local Search Algorithms - Designing, Implementing and Analyzing Effective Heuristics - Second International Workshop, SLS 2009, Proceedings
Pages	145-149
Number of pages	5
DOIs	https://doi.org/10.1007/978-3-642-03751-1_16
State	Published - 2009
Externally published	Yes
Event	2nd International Workshop on Engineering Stochastic Local Search Algorithms - Designing, Implementing and Analyzing Effective Heuristics, SLS 2009 - Brussels, Belgium Duration: Sep 3 2009 → Sep 4 2009

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5752 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	2nd International Workshop on Engineering Stochastic Local Search Algorithms - Designing, Implementing and Analyzing Effective Heuristics, SLS 2009
Country/Territory	Belgium
City	Brussels
Period	9/3/09 → 9/4/09

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Matthews, D. C., Sutton, A. M., Hains, D., & Whitley, L. D. (2009). Improved robustness through population variance in ant colony optimization. In Engineering Stochastic Local Search Algorithms - Designing, Implementing and Analyzing Effective Heuristics - Second International Workshop, SLS 2009, Proceedings (pp. 145-149). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5752 LNCS). https://doi.org/10.1007/978-3-642-03751-1_16

Improved robustness through population variance in ant colony optimization. / Matthews, David C.; Sutton, Andrew M.; Hains, Doug et al.
Engineering Stochastic Local Search Algorithms - Designing, Implementing and Analyzing Effective Heuristics - Second International Workshop, SLS 2009, Proceedings. 2009. p. 145-149 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5752 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Matthews, DC, Sutton, AM, Hains, D & Whitley, LD 2009, Improved robustness through population variance in ant colony optimization. in Engineering Stochastic Local Search Algorithms - Designing, Implementing and Analyzing Effective Heuristics - Second International Workshop, SLS 2009, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5752 LNCS, pp. 145-149, 2nd International Workshop on Engineering Stochastic Local Search Algorithms - Designing, Implementing and Analyzing Effective Heuristics, SLS 2009, Brussels, Belgium, 9/3/09. https://doi.org/10.1007/978-3-642-03751-1_16

Matthews DC, Sutton AM, Hains D, Whitley LD. Improved robustness through population variance in ant colony optimization. In Engineering Stochastic Local Search Algorithms - Designing, Implementing and Analyzing Effective Heuristics - Second International Workshop, SLS 2009, Proceedings. 2009. p. 145-149. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-03751-1_16

Matthews, David C. ; Sutton, Andrew M. ; Hains, Doug et al. / Improved robustness through population variance in ant colony optimization. Engineering Stochastic Local Search Algorithms - Designing, Implementing and Analyzing Effective Heuristics - Second International Workshop, SLS 2009, Proceedings. 2009. pp. 145-149 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Improved robustness through population variance in ant colony optimization

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