Building energy performance assessments are complex multi-criteria problems. Appropriate tools that can help designers explore design alternatives and assess the energy performance for choosing the most appropriate alternative are in high demand. In this paper, we present a newly developed integrated parametric Building Information Modeling (BIM)-based system to interact with cloud-based whole building energy performance simulation and daylighting tools to optimize building energy performance using a Multi-Objective Optimization (MOO) algorithm. This system enables designers to explore design alternatives using a visual programming interface, while assessing the energy performance of the design models to search for the most appropriate design. A case study of minimizing the energy use while maximizing the appropriate daylighting level of a residential building is provided to showcase the utility of the system and its workflow.
What if a CAD system could generate thousands of design options that all meet your specified goals? It’s no longer what if: it’s Project Dreamcatcher, the next generation of CAD. Dreamcatcher is a generative design system that enables designers to craft a definition of their design problem through goals and constraints. This information is used to synthesize alternative design solutions that meet the objectives. Designers are able to explore trade-offs between many alternative approaches and select design solutions for manufacture.