David Daily

Abstract

Energy efficient buildings are becoming more necessary to meet government standards, reduce operating costs, and curb emissions. However, designing efficient buildings is significantly complicated as designers must account for hundreds of design parameters across multiple domains. Simulation-based, design space exploration allows for designers to model a building's performance for multiple designs. These simulations can be computationally expensive and time consuming. This thesis explores trade-off analysis in building design space exploration through the use of multi-objective optimization software that seeks to quickly produce optimal designs. Three different techniques are developed producing optimal design configurations for each technique.