Facade Optimization For An Education Building Using Multi-objective Evolutionary Algorithms

Abstract

Architectural design of a facade, both at the aesthetic point of view and from the point of view of internal daylighting performance of the building, can be considered as a complex task. In this study, we implement a multi-objective evolutionary algorithm to formally exploration the process of reconstruction of the education building’s facade. The purpose of this research is to create a facade configuration by considering the size and location of elements and their materials when creating a suitable internal daylight distribution. The total construction cost of the building’s exterior and the daylight performance of the building’s interior are considered as objectives. The problem formulation includes two conflicting objectives, which are to increase daylighting aspect on each floor and reduce the total construction cost of the facade. To detect the approximation of Pareto fronts, including non-dominated solutions, we used a fast and elitist multi-objective genetic algorithm (NSGA-II). Computational and architectural results show that NSGA-II is efficient enough to demonstrate eligible facade design alternatives.