Solving network synthesis problems using ant colony optimisation

Marcus Randall; Elliot Tonkes

doi:10.1007/3-540-45517-5_1

Solving network synthesis problems using ant colony optimisation

Marcus Randall, Elliot Tonkes

Bond Business School

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

4 Citations (Scopus)

Abstract

Ant colony optimisation is a relatively new meta-heuristic search technique for solving optimisation problems. To date, much research has concentrated on solving standard benchmark problems such as the travelling salesman problem, quadratic assignment problem and the job sequencing problem. In this paper, we investigate the application of ant colony optimisation to practical telecommunication design and synthesis problems having real-world constraints. We consider a modelling approach suitable for ant colony optimisation implementation and compare the results to the simulated annealing meta-heuristic.

Original language	English
Title of host publication	Engineering of Intelligent Systems
Subtitle of host publication	IEA/AIE 2001
Editors	L Monostori, J Vancza, M Ali
Place of Publication	Berlin
Publisher	Springer
Pages	1-10
Number of pages	10
Volume	2070
ISBN (Print)	3540422196, 9783540422198
DOIs	https://doi.org/10.1007/3-540-45517-5_1
Publication status	Published - 2001
Event	14th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2001 - Budapest, Hungary Duration: 4 Jun 2001 → 7 Jun 2001

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2070
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Conference

Conference	14th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2001
Country/Territory	Hungary
City	Budapest
Period	4/06/01 → 7/06/01

Access to Document

10.1007/3-540-45517-5_1

Cite this

Randall, M., & Tonkes, E. (2001). Solving network synthesis problems using ant colony optimisation. In L. Monostori, J. Vancza, & M. Ali (Eds.), Engineering of Intelligent Systems: IEA/AIE 2001 (Vol. 2070, pp. 1-10). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2070). Springer. https://doi.org/10.1007/3-540-45517-5_1

Randall, Marcus ; Tonkes, Elliot. / Solving network synthesis problems using ant colony optimisation. Engineering of Intelligent Systems: IEA/AIE 2001. editor / L Monostori ; J Vancza ; M Ali. Vol. 2070 Berlin : Springer, 2001. pp. 1-10 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{69a428aef0f946658d72bd6f43bfdb00,

title = "Solving network synthesis problems using ant colony optimisation",

abstract = "Ant colony optimisation is a relatively new meta-heuristic search technique for solving optimisation problems. To date, much research has concentrated on solving standard benchmark problems such as the travelling salesman problem, quadratic assignment problem and the job sequencing problem. In this paper, we investigate the application of ant colony optimisation to practical telecommunication design and synthesis problems having real-world constraints. We consider a modelling approach suitable for ant colony optimisation implementation and compare the results to the simulated annealing meta-heuristic.",

author = "Marcus Randall and Elliot Tonkes",

year = "2001",

doi = "10.1007/3-540-45517-5_1",

language = "English",

isbn = "3540422196",

volume = "2070",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer",

pages = "1--10",

editor = "L Monostori and J Vancza and M Ali",

booktitle = "Engineering of Intelligent Systems",

address = "Germany",

note = "14th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2001 ; Conference date: 04-06-2001 Through 07-06-2001",

}

Randall, M & Tonkes, E 2001, Solving network synthesis problems using ant colony optimisation. in L Monostori, J Vancza & M Ali (eds), Engineering of Intelligent Systems: IEA/AIE 2001. vol. 2070, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2070, Springer, Berlin, pp. 1-10, 14th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2001, Budapest, Hungary, 4/06/01. https://doi.org/10.1007/3-540-45517-5_1

Solving network synthesis problems using ant colony optimisation. / Randall, Marcus; Tonkes, Elliot.
Engineering of Intelligent Systems: IEA/AIE 2001. ed. / L Monostori; J Vancza; M Ali. Vol. 2070 Berlin: Springer, 2001. p. 1-10 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2070).

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

TY - GEN

T1 - Solving network synthesis problems using ant colony optimisation

AU - Randall, Marcus

AU - Tonkes, Elliot

PY - 2001

Y1 - 2001

N2 - Ant colony optimisation is a relatively new meta-heuristic search technique for solving optimisation problems. To date, much research has concentrated on solving standard benchmark problems such as the travelling salesman problem, quadratic assignment problem and the job sequencing problem. In this paper, we investigate the application of ant colony optimisation to practical telecommunication design and synthesis problems having real-world constraints. We consider a modelling approach suitable for ant colony optimisation implementation and compare the results to the simulated annealing meta-heuristic.

AB - Ant colony optimisation is a relatively new meta-heuristic search technique for solving optimisation problems. To date, much research has concentrated on solving standard benchmark problems such as the travelling salesman problem, quadratic assignment problem and the job sequencing problem. In this paper, we investigate the application of ant colony optimisation to practical telecommunication design and synthesis problems having real-world constraints. We consider a modelling approach suitable for ant colony optimisation implementation and compare the results to the simulated annealing meta-heuristic.

UR - http://www.scopus.com/inward/record.url?scp=84947549488&partnerID=8YFLogxK

U2 - 10.1007/3-540-45517-5_1

DO - 10.1007/3-540-45517-5_1

M3 - Conference contribution

AN - SCOPUS:84947549488

SN - 3540422196

SN - 9783540422198

VL - 2070

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

SP - 1

EP - 10

BT - Engineering of Intelligent Systems

A2 - Monostori, L

A2 - Vancza, J

A2 - Ali, M

PB - Springer

CY - Berlin

T2 - 14th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2001

Y2 - 4 June 2001 through 7 June 2001

ER -

Randall M, Tonkes E. Solving network synthesis problems using ant colony optimisation. In Monostori L, Vancza J, Ali M, editors, Engineering of Intelligent Systems: IEA/AIE 2001. Vol. 2070. Berlin: Springer. 2001. p. 1-10. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-45517-5_1

Solving network synthesis problems using ant colony optimisation

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this