BIM-based Parametric Building Energy Performance Multi- Objective Optimization Mohammad Rahmani Asl 1 , Michael Bergin 2 , Adam Menter 3 , Wei Yan 4 1 PhD Candidate, Department of Architecture, Texas A&M University 2 Research Scientist, Autodesk Inc. 3 Sustainability Education Program Manager, Autodesk Inc. 4 Associate Professor, Department of Architecture, Texas A&M University 1 sites.google.com/site/bimsimgroup/people/students/mohammad-rahmani-asl 2 www.autodeskresearch.com/people/michaelbergin 3 www.adammenter.com/ 4 faculty.arch.tamu.edu/wyan 1,4 {mrah|wyan}@tamu.edu 2,3 {michael.bergin|adam.menter}@autodesk.com 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. Keywords: Building Energy Performance Analysis, Building Information Model (BIM), Parametric Modelling, Parametric Energy Simulation, Multi-objective Optimization INTRODUCTION Due to the considerable impact of buildings on the environment, it is essential for designers to recognize the importance of improving or optimizing building energy performance in the early design stage. En- ergy performance-based design is a highly complex and labor-intensive process. Designers deal with a complex Multi-Objective Optimization (MOO) prob- lem to minimize capital and operating costs while maintaining occupants comfort (Wang et al., 2005; Wright et al., 2002). This complexity comes from the large number of interrelated parameters involved in BIM - Volume 2 - eCAADe 32 | 455