Multi-objective optimization of cellular fenestration by an evolutionary algorithm

Citation

Wright JA, Brownlee A, Mourshed MM & Wang M (2014) Multi-objective optimization of cellular fenestration by an evolutionary algorithm. Journal of Building Performance Simulation, 7 (1), pp. 33-51. https://doi.org/10.1080/19401493.2012.762808

Abstract
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.

Keywords
façade optimization; evolutionary algorithms; multi\-objective optimization; local and global sensitivity analysis

Journal
Journal of Building Performance Simulation: Volume 7, Issue 1

People

Dr Sandy Brownlee

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