Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 263171
Loughborough University

Loughborough University Institutional Repository

Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/10275

Title: Solution analysis in multi-objective optimization
Authors: Brownlee, Alexander E.I.
Wright, Jonathan A.
Issue Date: 2012
Publisher: Loughborough University © IBPSA-England
Citation: BROWNLEE, A.E.I. and WRIGHT, J.A., 2012. Solution analysis in multi-objective optimization. Building Simulation and Optimization 2012, Loughborough, UK, 10-11 September 2012, pp. 317 - 324.
Abstract: Recent years have seen a growth in the use of evolutionary algorithms to optimize multi-objective building design problems. The aim is to find the Pareto optimal trade-off between conflicting design objectives such as capital cost and operational energy use. Analysis of the resulting set of solutions can be difficult, particularly where there are a large number (possibly hundreds) of design variables to consider. This paper reviews existing approaches to analysis of the Pareto front. It then introduces new approach to the analysis of the trade-off, based on a simple rank- ordering of the objectives, together with the correlation between objectives and problem variables. This allows analysis of the trade-off between the design objectives and variables. The approach is demonstrated for an example building, covering the different relationships that can exist between variables and the objectives.
Description: This paper was presented at the First Building Simulation and Optimization Conference, Loughborough, UK, 10-11 September 2012 [© IBPSA-England].
Version: Published
URI: https://dspace.lboro.ac.uk/2134/10275
ISBN: 9781897911426
Appears in Collections:Conference Papers (Civil and Building Engineering)

Files associated with this item:

File Description SizeFormat
Solution analysis.pdf1.02 MBAdobe PDFView/Open

 

SFX Query

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.