Multi-objective optimisation in scientific workflow

Simple item page
dc.contributor.authorNguyen, Hoang Anh
dc.contributor.authorvan Iperen, Zane
dc.contributor.authorRaghunath, Sreekanth
dc.contributor.authorAbramson, David
dc.contributor.authorKipouros, Timoleon
dc.contributor.authorSomasekharan, Sandeep
dc.date.accessioned2017-07-07T14:38:14Z
dc.date.available2017-07-07T14:38:14Z
dc.date.issued2017-06-09
dc.description.abstractEngineering 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.en_UK
dc.identifier.citationHoang Anh Nguyen, Zane van Iperen, Sreekanth Raghunath, David Abramson, Timoleon Kipouros, Sandeep Somasekharan, Multi-objective optimisation in scientific workflow, Procedia Computer Science, Volume 108, 2017, Pages 1443-1452en_UK
dc.identifier.issn1877-0509
dc.identifier.urihttp://dx.doi.org/10.1016/j.procs.2017.05.213
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/12173
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution-Non-Commercial-No Derivatives 4.0 Unported (CC BY-NC-ND 4.0). You are free to: Share — copy and redistribute the material in any medium or format. The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. Information: Non-Commercial — You may not use the material for commercial purposes. No Derivatives — If you remix, transform, or build upon the material, you may not distribute the modified material. No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
dc.subjectMulti-objective optimisationen_UK
dc.subjectScientific Workflowen_UK
dc.subjectEngineering Designen_UK
dc.titleMulti-objective optimisation in scientific workflowen_UK
dc.typeArticleen_UK

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Multi-objective_optimisation_in_scientific_workflow-2017.pdf
Size:
1.17 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.79 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Staff publications (SATM)