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Multi-objective optimization of cellular fenestration by an evolutionary algorithm

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journal contribution
posted on 31.01.2013, 15:03 by Jonathan WrightJonathan Wright, Sandy Brownlee, Monjur Mourshed
This paper describes the multi-objective optimized design of fenestration that is based on the façade of the building being divided into a number of small regularly spaced cells. The minimization of energy use and capital cost by a multi-objective genetic algorithm was investigated for; two alternative problem encodings (bit-string and integer); the application of constraint functions to control the aspect ratio of the windows; and the seeding of the search with feasible design solutions. It is concluded that the optimization approach is able to find near locally Pareto optimal solutions that have innovative architectural forms. Confidence in the optimality of the solutions was gained through repeated trail optimizations and a local search and sensitivity analysis. It was also concluded that seeding the optimization with feasible solutions was important in obtaining the optimum solutions when the window aspect ratio was constrained.

History

School

  • Architecture, Building and Civil Engineering

Citation

WRIGHT, J., BROWNLEE, A. and MOURSHED, M. (in press). Multi-objective optimization of cellular fenestration by an evolutionary algorithm. Journal of Building Performance Simulation, DOI: 10.1080/19401493.2012.762808

Publisher

Taylor & Francis (Routledge) © International Building Performance Simulation Association (IBPSA)

Version

SMUR (Submitted Manuscript Under Review)

Publication date

2013

Notes

This article was submitted for publication in the Journal of Building Performance Simulation [Taylor & Francis (Routledge) © International Building Performance Simulation Association (IBPSA)]. Journal of Building Performance Simulation is available online at http://www.tandfonline.com/doi/full/10.1080/19401493.2012.762808.

ISSN

1940-1493

Language

en