Conference Proceeding

Solution Analysis in Multi-Objective Optimization



Brownlee A & Wright JA (2012) Solution Analysis in Multi-Objective Optimization. In: Wright J & Cook M (eds.) Proceedings of the 2012 Building Simulation and Optimization Conference. First Building Simulation and Optimization Conference, Loughborough, 10.09.2012-11.09.2012. Loughborough: Loughborough University, pp. 317-324.

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.

Publication date31/12/2012
Publication date online30/09/2012
Related URLs
PublisherLoughborough University
Publisher URL
Place of publicationLoughborough
ConferenceFirst Building Simulation and Optimization Conference
Conference locationLoughborough

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Dr Sandy Brownlee

Dr Sandy Brownlee

Senior Lecturer in Computing Science, Computing Science and Mathematics - Division