Multi-objective optimisation in scientific workflow

Nguyen, Hoang Anh, Van Iperen, Zane, Raghunath, Sreekanth, Abramson, David, Kipouros, Timoleon and Somasekharan, Sandeep (2017). Multi-objective optimisation in scientific workflow. In: International Conference On Computational Science (ICCS 2017). International Conference on Computational Science (ICCS), Zurich, Switzerland, (1443-1452). 12 - 14 June 2017. doi:10.1016/j.procs.2017.05.213

Author Nguyen, Hoang Anh
Van Iperen, Zane
Raghunath, Sreekanth
Abramson, David
Kipouros, Timoleon
Somasekharan, Sandeep
Title of paper Multi-objective optimisation in scientific workflow
Conference name International Conference on Computational Science (ICCS)
Conference location Zurich, Switzerland
Conference dates 12 - 14 June 2017
Proceedings title International Conference On Computational Science (ICCS 2017)   Check publisher's open access policy
Journal name Procedia Computer Science   Check publisher's open access policy
Series Procedia Computer Science
Place of Publication Amsterdam, Netherlands
Publisher Elsevier BV
Publication Year 2017
Sub-type Fully published paper
DOI 10.1016/j.procs.2017.05.213
Open Access Status DOI
ISSN 1877-0509
Volume 108
Start page 1443
End page 1452
Total pages 10
Language eng
Abstract/Summary Engineering design is typically a complex process that involves finding a set of designs satisfying various performance criteria. As a result, optimisation algorithms dealing with only single-objective are not sufficient to deal with many real-life problems. Meanwhile, scientific workflows have been shown to be an effective technology for automating and encapsulating scientific processes. While optimisation algorithms have been integrated into workflow tools, they are generally single-objective. This paper first presents our latest development to incorporate multi-objective optimisation algorithms into scientific workflows. We demonstrate the efficacy of these capabilities with the formulation of a three-objective aerodynamics optimisation problem. We target to improve the aerodynamic characteristics of a typical 2D airfoil profile considering also the laminar-turbulent transition location for more accurate estimation of the total drag. We deploy two different heuristic optimisation algorithms and compare the preliminary results.
Subjects 1700 Computer Science
Keyword Engineering Design
Multi-objective optimisation
Scientific Workflow
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status UQ

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