Multi-objective parallel tabu search

Daniel Jaeggi; Chris Asselin-Miller; Geoff Parks; Timoleon Kipouros; Theo Bell; John Clarkson

doi:10.1007/978-3-540-30217-9_74

Multi-objective parallel tabu search

Daniel Jaeggi^*, Chris Asselin-Miller, Geoff Parks, Timoleon Kipouros, Theo Bell, John Clarkson

^*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volume › Chapter › Scientific › peer-review

21 Citations (Scopus)

Abstract

This paper describes the implementation of a parallel Tabu Search algorithm for multi-objective continuous optimisation problems. We compare our new algorithm with a leading multi-objective Genetic Algorithm and find it exhibits comparable performance on standard benchmark problems. In addition, for certain problem types, we expect Tabu Search to outperform other algorithms and present preliminary results from an aerodynamic shape optimisation problem. This is a real-world, highly constrained, computationally demanding design problem which requires efficient optimisation algorithms that can be run on parallel computers: with this approach optimisation algorithms are able to play a part in the design cycle.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Editors	Xin Yao, John A. Bullinaria, Jonathan Rowe, Peter Tino, Ata Kaban, Edmund Burke, Jose A. Lozano, Jim Smith, Juan J. Merelo-Guervos, Hans-Paul Schwefel
Publisher	Springer
Pages	732-741
Number of pages	10
ISBN (Print)	3540230920, 9783540230922
DOIs	https://doi.org/10.1007/978-3-540-30217-9_74
Publication status	Published - 2004
Externally published	Yes

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3242
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

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10.1007/978-3-540-30217-9_74

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Jaeggi, D., Asselin-Miller, C., Parks, G., Kipouros, T., Bell, T., & Clarkson, J. (2004). Multi-objective parallel tabu search. In X. Yao, J. A. Bullinaria, J. Rowe, P. Tino, A. Kaban, E. Burke, J. A. Lozano, J. Smith, J. J. Merelo-Guervos, & H.-P. Schwefel (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 732-741). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3242). Springer. https://doi.org/10.1007/978-3-540-30217-9_74

Jaeggi, Daniel ; Asselin-Miller, Chris ; Parks, Geoff et al. / Multi-objective parallel tabu search. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). editor / Xin Yao ; John A. Bullinaria ; Jonathan Rowe ; Peter Tino ; Ata Kaban ; Edmund Burke ; Jose A. Lozano ; Jim Smith ; Juan J. Merelo-Guervos ; Hans-Paul Schwefel. Springer, 2004. pp. 732-741 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "This paper describes the implementation of a parallel Tabu Search algorithm for multi-objective continuous optimisation problems. We compare our new algorithm with a leading multi-objective Genetic Algorithm and find it exhibits comparable performance on standard benchmark problems. In addition, for certain problem types, we expect Tabu Search to outperform other algorithms and present preliminary results from an aerodynamic shape optimisation problem. This is a real-world, highly constrained, computationally demanding design problem which requires efficient optimisation algorithms that can be run on parallel computers: with this approach optimisation algorithms are able to play a part in the design cycle.",

author = "Daniel Jaeggi and Chris Asselin-Miller and Geoff Parks and Timoleon Kipouros and Theo Bell and John Clarkson",

year = "2004",

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

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pages = "732--741",

editor = "Xin Yao and Bullinaria, {John A.} and Jonathan Rowe and Peter Tino and Ata Kaban and Edmund Burke and Lozano, {Jose A.} and Jim Smith and Merelo-Guervos, {Juan J.} and Hans-Paul Schwefel",

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Jaeggi, D, Asselin-Miller, C, Parks, G, Kipouros, T, Bell, T & Clarkson, J 2004, Multi-objective parallel tabu search. in X Yao, JA Bullinaria, J Rowe, P Tino, A Kaban, E Burke, JA Lozano, J Smith, JJ Merelo-Guervos & H-P Schwefel (eds), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3242, Springer, pp. 732-741. https://doi.org/10.1007/978-3-540-30217-9_74

Multi-objective parallel tabu search. / Jaeggi, Daniel; Asselin-Miller, Chris; Parks, Geoff et al.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). ed. / Xin Yao; John A. Bullinaria; Jonathan Rowe; Peter Tino; Ata Kaban; Edmund Burke; Jose A. Lozano; Jim Smith; Juan J. Merelo-Guervos; Hans-Paul Schwefel. Springer, 2004. p. 732-741 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3242).

Research output: Chapter in Book/Conference proceedings/Edited volume › Chapter › Scientific › peer-review

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T1 - Multi-objective parallel tabu search

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AU - Parks, Geoff

AU - Kipouros, Timoleon

AU - Bell, Theo

AU - Clarkson, John

PY - 2004

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AB - This paper describes the implementation of a parallel Tabu Search algorithm for multi-objective continuous optimisation problems. We compare our new algorithm with a leading multi-objective Genetic Algorithm and find it exhibits comparable performance on standard benchmark problems. In addition, for certain problem types, we expect Tabu Search to outperform other algorithms and present preliminary results from an aerodynamic shape optimisation problem. This is a real-world, highly constrained, computationally demanding design problem which requires efficient optimisation algorithms that can be run on parallel computers: with this approach optimisation algorithms are able to play a part in the design cycle.

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Jaeggi D, Asselin-Miller C, Parks G, Kipouros T, Bell T, Clarkson J. Multi-objective parallel tabu search. In Yao X, Bullinaria JA, Rowe J, Tino P, Kaban A, Burke E, Lozano JA, Smith J, Merelo-Guervos JJ, Schwefel HP, editors, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer. 2004. p. 732-741. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-30217-9_74

Multi-objective parallel tabu search

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