Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Multi-objective optimization of cellular fenestration by an evolutionary algorithm

Wright, Jonathan A., Brownlee, Alexander E. I., Mourshed, Monjur and Wang, Mengchao 2014. Multi-objective optimization of cellular fenestration by an evolutionary algorithm. Journal of Building Performance Simulation 7 (1) , pp. 33-51. 10.1080/19401493.2012.762808

Full text not available from this repository.


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.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Subjects: T Technology > TH Building construction
Uncontrolled Keywords: façade optimization; evolutionary algorithms; multi-objective optimization; local and global sensitivity analysis
Publisher: Taylor & Francis
ISSN: 1940-1493
Last Modified: 20 Feb 2019 17:06

Citation Data

Cited 36 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item