Vectorized candidate selection for parallel ant colony optimization

Joshua Peake; Martyn Amos; Paris Yiapanis; Huw Lloyd

doi:10.1145/3205651.3208274

Vectorized candidate selection for parallel ant colony optimization

Joshua Peake, Martyn Amos, Paris Yiapanis, Huw Lloyd

Computer Information Sciences Department

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

11 Citations (Scopus)

Abstract

Ant Colony Optimization (ACO) is a well-established nature-inspired heuristic, and parallel versions of the algorithm now exist to take advantage of emerging high-performance computing processors. However, careful attention must be paid to parallel components of such implementations if the full benefit of these platforms is to be obtained. One such component of the ACO algorithm is next node selection, which presents unique challenges in a parallel setting. In this paper, we present a new node selection method for ACO, Vectorized Candidate Set Selection (VCSS), which achieves significant speedup over existing selection methods on a test set of Traveling Salesman Problem instances.

Original language	English
Title of host publication	GECCO '18 Proc. Genetic and Evolutionary Computation Conference Companion (GECCO '18), July 15-19 2018, Kyoto, Japan
Subtitle of host publication	Proceedings of the Genetic and Evolutionary Computation Conference Companion
Editors	Hernan Aquirre
Publisher	ACM
Pages	1300-1306
Number of pages	7
ISBN (Print)	9781450357647
DOIs	https://doi.org/10.1145/3205651.3208274
Publication status	Published - 6 Jul 2018
Event	Genetic and Evolutionary Computation Conference 2018 - Kyoto, Japan Duration: 15 Jul 2018 → 19 Jul 2018

Conference

Conference	Genetic and Evolutionary Computation Conference 2018
Abbreviated title	GECCO '18
Country/Territory	Japan
City	Kyoto
Period	15/07/18 → 19/07/18

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10.1145/3205651.3208274

Cite this

Peake, J., Amos, M., Yiapanis, P., & Lloyd, H. (2018). Vectorized candidate selection for parallel ant colony optimization. In H. Aquirre (Ed.), GECCO '18 Proc. Genetic and Evolutionary Computation Conference Companion (GECCO '18), July 15-19 2018, Kyoto, Japan: Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 1300-1306). ACM. https://doi.org/10.1145/3205651.3208274

Peake, Joshua ; Amos, Martyn ; Yiapanis, Paris et al. / Vectorized candidate selection for parallel ant colony optimization. GECCO '18 Proc. Genetic and Evolutionary Computation Conference Companion (GECCO '18), July 15-19 2018, Kyoto, Japan: Proceedings of the Genetic and Evolutionary Computation Conference Companion . editor / Hernan Aquirre. ACM, 2018. pp. 1300-1306

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title = "Vectorized candidate selection for parallel ant colony optimization",

abstract = "Ant Colony Optimization (ACO) is a well-established nature-inspired heuristic, and parallel versions of the algorithm now exist to take advantage of emerging high-performance computing processors. However, careful attention must be paid to parallel components of such implementations if the full benefit of these platforms is to be obtained. One such component of the ACO algorithm is next node selection, which presents unique challenges in a parallel setting. In this paper, we present a new node selection method for ACO, Vectorized Candidate Set Selection (VCSS), which achieves significant speedup over existing selection methods on a test set of Traveling Salesman Problem instances.",

author = "Joshua Peake and Martyn Amos and Paris Yiapanis and Huw Lloyd",

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note = "Genetic and Evolutionary Computation Conference 2018, GECCO '18 ; Conference date: 15-07-2018 Through 19-07-2018",

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Peake, J, Amos, M, Yiapanis, P & Lloyd, H 2018, Vectorized candidate selection for parallel ant colony optimization. in H Aquirre (ed.), GECCO '18 Proc. Genetic and Evolutionary Computation Conference Companion (GECCO '18), July 15-19 2018, Kyoto, Japan: Proceedings of the Genetic and Evolutionary Computation Conference Companion . ACM, pp. 1300-1306, Genetic and Evolutionary Computation Conference 2018, Kyoto, Japan, 15/07/18. https://doi.org/10.1145/3205651.3208274

Vectorized candidate selection for parallel ant colony optimization. / Peake, Joshua; Amos, Martyn; Yiapanis, Paris et al.
GECCO '18 Proc. Genetic and Evolutionary Computation Conference Companion (GECCO '18), July 15-19 2018, Kyoto, Japan: Proceedings of the Genetic and Evolutionary Computation Conference Companion . ed. / Hernan Aquirre. ACM, 2018. p. 1300-1306.

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

TY - GEN

T1 - Vectorized candidate selection for parallel ant colony optimization

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AU - Amos, Martyn

AU - Yiapanis, Paris

AU - Lloyd, Huw

PY - 2018/7/6

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N2 - Ant Colony Optimization (ACO) is a well-established nature-inspired heuristic, and parallel versions of the algorithm now exist to take advantage of emerging high-performance computing processors. However, careful attention must be paid to parallel components of such implementations if the full benefit of these platforms is to be obtained. One such component of the ACO algorithm is next node selection, which presents unique challenges in a parallel setting. In this paper, we present a new node selection method for ACO, Vectorized Candidate Set Selection (VCSS), which achieves significant speedup over existing selection methods on a test set of Traveling Salesman Problem instances.

AB - Ant Colony Optimization (ACO) is a well-established nature-inspired heuristic, and parallel versions of the algorithm now exist to take advantage of emerging high-performance computing processors. However, careful attention must be paid to parallel components of such implementations if the full benefit of these platforms is to be obtained. One such component of the ACO algorithm is next node selection, which presents unique challenges in a parallel setting. In this paper, we present a new node selection method for ACO, Vectorized Candidate Set Selection (VCSS), which achieves significant speedup over existing selection methods on a test set of Traveling Salesman Problem instances.

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DO - 10.1145/3205651.3208274

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EP - 1306

BT - GECCO '18 Proc. Genetic and Evolutionary Computation Conference Companion (GECCO '18), July 15-19 2018, Kyoto, Japan

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Y2 - 15 July 2018 through 19 July 2018

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Peake J, Amos M, Yiapanis P, Lloyd H. Vectorized candidate selection for parallel ant colony optimization. In Aquirre H, editor, GECCO '18 Proc. Genetic and Evolutionary Computation Conference Companion (GECCO '18), July 15-19 2018, Kyoto, Japan: Proceedings of the Genetic and Evolutionary Computation Conference Companion . ACM. 2018. p. 1300-1306 doi: 10.1145/3205651.3208274

Vectorized candidate selection for parallel ant colony optimization

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