Environmental parametric multi-objective optimization for high performance facade design

Abstract

This paper demonstrates the applicability of a data-integrated and user-friendly Multi-Objective Optimization (MOO) method within the Grasshopper (GH) parametric design interface which supports early stage design decision making for High Performance Building (HPB) façade. With multiple environmental objectives optimized and multiple geometric parameters adjusted in the same intuitive design space, designers with limited knowledge on scripting could easily set up the nodes simultaneously when the design is carried out to achieve the efficiency in HPB design optimization. An experiment utilizing the method, with DIVA as the environmental simulator and Octopus as the MOO solver, is demonstrated for rational daylight distribution, balanced solar heat gain and reduced energy use intensity. The findings show both potentials and limitations of the proposed method.