Understanding the pheromone system within ant colony optimization

Stephen Gilmour; Mark Dras

doi:10.1007/11589990_81

Understanding the pheromone system within ant colony optimization

Stephen Gilmour^*, Mark Dras

^*Corresponding author for this work

School of Computing

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

12 Citations (Scopus)

Abstract

Ant Colony Optimization (ACO) is a collection of metaheuristics inspired by foraging in ant colonies, whose aim is to solve combinatorial optimization problems. We identify some principles behind the metaheuristics' rules; and we show that ensuring their application, as a correction to a published algorithm for the vertex cover problem, leads to a statistically significant improvement in empirical results.

Original language	English
Title of host publication	AI 2005: Advances in Artificial Intelligence
Subtitle of host publication	18th Australian Joint Conference on Artificial Intelligence, Sydney, Australia, December 5-9, 2005. Proceedings
Editors	Shichao Zhang, Ray Jarvis
Place of Publication	Berlin; Heidelberg
Publisher	Springer, Springer Nature
Pages	786-789
Number of pages	4
Volume	3809 LNAI
ISBN (Electronic)	9783540316527
ISBN (Print)	3540304622, 9783540304623
DOIs	https://doi.org/10.1007/11589990_81
Publication status	Published - 2005
Event	18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence - Sydney, Australia Duration: 5 Dec 2005 → 9 Dec 2005

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3809 LNAI
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Other

Other	18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence
Country/Territory	Australia
City	Sydney
Period	5/12/05 → 9/12/05

Access to Document

10.1007/11589990_81

Cite this

Gilmour, S., & Dras, M. (2005). Understanding the pheromone system within ant colony optimization. In S. Zhang, & R. Jarvis (Eds.), AI 2005: Advances in Artificial Intelligence: 18th Australian Joint Conference on Artificial Intelligence, Sydney, Australia, December 5-9, 2005. Proceedings (Vol. 3809 LNAI, pp. 786-789). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3809 LNAI). Springer, Springer Nature. https://doi.org/10.1007/11589990_81

Gilmour, Stephen ; Dras, Mark. / Understanding the pheromone system within ant colony optimization. AI 2005: Advances in Artificial Intelligence: 18th Australian Joint Conference on Artificial Intelligence, Sydney, Australia, December 5-9, 2005. Proceedings. editor / Shichao Zhang ; Ray Jarvis. Vol. 3809 LNAI Berlin; Heidelberg : Springer, Springer Nature, 2005. pp. 786-789 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Understanding the pheromone system within ant colony optimization",

abstract = "Ant Colony Optimization (ACO) is a collection of metaheuristics inspired by foraging in ant colonies, whose aim is to solve combinatorial optimization problems. We identify some principles behind the metaheuristics' rules; and we show that ensuring their application, as a correction to a published algorithm for the vertex cover problem, leads to a statistically significant improvement in empirical results.",

author = "Stephen Gilmour and Mark Dras",

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doi = "10.1007/11589990_81",

language = "English",

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pages = "786--789",

editor = "Shichao Zhang and Ray Jarvis",

booktitle = "AI 2005: Advances in Artificial Intelligence",

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note = "18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence ; Conference date: 05-12-2005 Through 09-12-2005",

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Gilmour, S & Dras, M 2005, Understanding the pheromone system within ant colony optimization. in S Zhang & R Jarvis (eds), AI 2005: Advances in Artificial Intelligence: 18th Australian Joint Conference on Artificial Intelligence, Sydney, Australia, December 5-9, 2005. Proceedings. vol. 3809 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3809 LNAI, Springer, Springer Nature, Berlin; Heidelberg, pp. 786-789, 18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence, Sydney, Australia, 5/12/05. https://doi.org/10.1007/11589990_81

Understanding the pheromone system within ant colony optimization. / Gilmour, Stephen; Dras, Mark.
AI 2005: Advances in Artificial Intelligence: 18th Australian Joint Conference on Artificial Intelligence, Sydney, Australia, December 5-9, 2005. Proceedings. ed. / Shichao Zhang; Ray Jarvis. Vol. 3809 LNAI Berlin; Heidelberg: Springer, Springer Nature, 2005. p. 786-789 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3809 LNAI).

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

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AB - Ant Colony Optimization (ACO) is a collection of metaheuristics inspired by foraging in ant colonies, whose aim is to solve combinatorial optimization problems. We identify some principles behind the metaheuristics' rules; and we show that ensuring their application, as a correction to a published algorithm for the vertex cover problem, leads to a statistically significant improvement in empirical results.

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M3 - Conference proceeding contribution

AN - SCOPUS:33745610088

SN - 3540304622

SN - 9783540304623

VL - 3809 LNAI

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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EP - 789

BT - AI 2005: Advances in Artificial Intelligence

A2 - Zhang, Shichao

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PB - Springer, Springer Nature

CY - Berlin; Heidelberg

T2 - 18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence

Y2 - 5 December 2005 through 9 December 2005

ER -

Gilmour S, Dras M. Understanding the pheromone system within ant colony optimization. In Zhang S, Jarvis R, editors, AI 2005: Advances in Artificial Intelligence: 18th Australian Joint Conference on Artificial Intelligence, Sydney, Australia, December 5-9, 2005. Proceedings. Vol. 3809 LNAI. Berlin; Heidelberg: Springer, Springer Nature. 2005. p. 786-789. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11589990_81

Understanding the pheromone system within ant colony optimization

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